To put it in simple language, Sentiment Analysis reads – enormously massive data generated online by consumers who are expressing their feelings and attitudes about brands, products or services on the internet, through various social media sites, review portals, website etc.
Sentiment Analysis distils – expressed opinions haphazardly scattered across various online outlets into coherent information by breaking them down into three recognizable states of sentiments such as –Positive, Neutral & Negative
Sentiment Analysis it is also called – Opinion Mining – it is an automated data mining process aimed at uncovering and making sense of people’s emotions, moods and takes on a given topic or subject.
It is also possible to further segregate sentiments into five stages such as Very Positive, Positive, Neutral, Negative and Very Negative. For those interested in understanding the intensity and frequency of these categories, with new AI technologies available today, they can be measured on a scale of 1 to 100 as well.
Sentiment Analysis is a part of Natural Language Processing (NLP), which in turn is a component of Artificial Intelligence (AI).
Network Visualization of Sentiment Analysis at work
Human beings generate 2.5 quintillion bytes of data every day around the world.
It is humanly impossible to manually read, interpret and derive useful information out of this massive data accumulated.
Sentiment analysis is a tool that offers a solution to this daunting challenge by identifying the emotions and moods behind what consumers expressed, and assigning them categories to convey a clearer picture of what they feel.
Sentiment Analysis sheds light on the attributes of expressions and opinions as given below
- Polarity Classification – Categorize opinions on whether they are Positive, Negative or Normative
- Subjectivity Classification – Nature of topics that people are discussing
- Opinion Holder Recognition – Identifies from whom the opinions generate
USES & APPLICATIONS
Social media monitoring
Social media sentiment Analysis monitors what people say about your business on various social media outlets.
Example – Nike released a new campaign ad featuring Colin Kaepernick, it received widely polarized opinions. Some supported it fervently while others were firmly against it, to the point that they decided to burn their Nike products.
Nike’s response would have to be based on an informed choice of knowing whether their campaign is hurting their overall brand image, which would be made possible by monitoring consumers’ reactions on Social Media through sentiment analysis.
Sentiment Analysis on Social Media allows you to
- Stay informed about strong opinions
- Know what are the trending topics and news
- Measure your brand’s reputation on social media
- Follow consumers’ conversations after significant events. E.g. Product launch, an introduction of new features etc.
- Keep track of your competitors’ activities and what people say about them
Sentiment Analysis used for brand monitoring follows online conversations on various forums such as blogs, articles, reviews, discussions etc. beyond social media channels; and discerns views that are voiced and expressed.
Example – Twitter sentiment analysis uses various feature sets and methods to update itself with users’ attitudes towards its service and address issues and pain points raised by them. Twitter is currently considering adding an edit feature for tweets that are posted, which is, likely, the outcome of Twitter’s brand sentiment monitoring to ensure consumers using its service remain engaged and satisfied.
Using sentiment analysis for brand monitoring enables you to
- Continually analyze discussions and conversations about your brand as and when it is happening on the internet.
- Monitor extreme opinions and address them before they escalate into a disaster
- Immediately manage a crisis, if it happens and find a pro-active PR solution
- Track concerns raised about your products and services
- Know the status of your brand online presence with insights and analytics
- Stay informed about your brand reputation evolution
Customer feedbacks & Support
Another useful application of sentiment analysis is to apply it on surveys and customer support interactions to decipher customer feedbacks and offer support. While Net Promoter Score (NPS) is useful for this function, Sentiment Analysis takes it a step further and provides clearer insights, enabling brands to offer impressive customer service experiences across various channels including social media handles, chatbots, chat support, telephonic and video support, and ultimately retain their loyalty.
Example – Netflix received a lot of unhappy customer feedbacks when it attempted to raise its subscription cost by $6 without providing any service upgrade. Consumers voicing their sentiments and criticizing the network gained significant momentum online, prompting the company to change its decision.
When sentiment analysis is used to listen to Voice of Customers (VoC) and offer Customer Support
- You gain access to consumers’ opinions filtered by segmentation or by specific aspects of the business.
- You become more perceptive and come up with better questions to ask in future surveys.
- You listen to consumers better and understand the nuances that cause shifts in choice and preference.
- You respond more efficiently and quickly to change in trends and consumers’ sentiments
- You can analyze all customer support queries and automatically detect unhappy clients and promptly respond to them
Workforce analytics and voice of the employee
Sentiment analysis within the organization enables you to monitor employee surveys with specific keywords and segmentation to get a clear picture of employee sentiments over time and stay alert if it reveals discontent, allowing you to manage it promptly. It is highly advantageous in high-stress and high-risk industries like mining, public transport etc.
Example – Internal surveys and reviews are not conducted daily and hence, issues that may require immediate attention may surface long after it could be resolved, especially in large organizations. Sentiment Analysis on employee feedbacks (VoE) allows a business to monitor employees grievances and issues in real-time.
- You stay connected to employees and hear their concerns, enabling you to address them and make them feel appreciated and valued.
- You monitor VoE in real-time instead of waiting for insights from reviews and surveys.
We live in a fast-paced world where change is the only thing that is constant. Contents and products have to continually evolve to keep up with the changing environment and trends. For this to happen, they must be previewed and tested before releasing them into the market. Sentiment Analysis conducted in test market provide insights into consumers’ emotional responses, and companies use the results derived for changing, upgrading and meeting consumers’ needs and wants.
Sentiment Analysis of product analytics allows you to
- Analyze vast amount of product feedbacks
- Monitor online or social media comments about the product
- Immediately receive relevant conversations about products
- Keep a tab on those who criticize the products and see whether their views have substance
- Segment product target market
- Gain detailed insights into product performance
Market research and analysis
Sentiment Analysis is a useful tool for conducting market research and analysis to explore a new market or predict future trends or perform competitor analysis.
When Twitter creators, Evan Williams and Biz Stone decided to create a platform to browse, create and share podcasts in 2005, they were a bit ahead of time as podcasting took more than a decade later to become a mainstream medium.
They studied the market and users’ sentiments and came to learn Facebook’s limitation – its newsfeed tends to be cluttered making people feel overwhelmed by it. They decided to create a Social Networking site that is dedicated to sharing of information and came up with Twitter – whose ubiquitous success story needs no further description.
Sentiment analysis in market research and analysis allows you to
- Utilize new sources of information
- Measure and quantify available information
- Access real-time market data.
- Automated updates
- Generate market insights
Why does it matter
It is estimated that 80% of the data available in the world today is unorganized and most of them are in the form of texts. Sentiment analysis is an automation process utilized to make sense of this large amassed data and come up with actionable insights – which would have been otherwise undecipherable.
The Essential Attributes of Sentiment Analysis Are –
- Real-time Analysis
How can you conduct emotional and sentiment analysis for your brands, products and services or your employees?
Entropik Tech’s affectLab uses emotion recognition technologies such as Brainwave mapping, Facial Coding and Eye Tracking, Voice and Text Analysis to generate Emotion Analytics for consumer brands.
Test consumer sentiments towards your brand with our SaaS platform, affectlab. Start with our Free Trial.