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Top Benefits of using Tone Analysis and Sentiments Analysis for your Business

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Consumer feedback about products or a brand in general will provide businesses necessary context to evaluate- and maybe even re-strategize- their marketing and communications strategy. Sentiment and tone analysis help businesses understand customer insights that can be provided on various platforms like websites, social media channels, emails and much more. These insights will point out what the target audience expects from the business/product, any areas of improvement and even positive feedback that can then propel others to try the service!

This article will take you through the concept of tone and sentiment analysis and show you its importance from a business perspective.

  • Overview of Sentiment and Tone Analysis
    Consumer feedback is often received in raw and unstructured format. This data can be wrongly interpreted by human employees, which can then have an impact on business relations. Additionally, multiple avenues of feedback make it difficult to collect and analyze every piece of information. AI can help transform this raw data into structured data and then use Natural Language Processing (NLP) to understand the sentiment behind every feedback. This information can be used by businesses to produce better products, services, and experiences.
  • Sentiment Analysis
    Sentiment analysis (in customer written communication) is also known as ‘Mining Opinion’. This process uses Artificial Intelligence (AI) tools to extract, analyze and understand the emotion underneath a specific text based opinion. This technology performs a contextual mining of text, by studying consumer feedback across various platforms, to help businesses understand whether the underlying customer sentiment behind the feedback provided is neutral, positive or negative.
  • Tone Analysis
    Tone Analysis (in customer audio communication) analyzes the pitch of the speaker to extract information from these digital audio signals and derive its underlying emotion.
    An excellent example of tone analysis is monitoring tele-customer service and support conversations. Their tones can be analyzed to detect satisfaction, frustration, anger, happiness, intention, urgency and much more. Understanding a customer’s tone can help build dialog strategies for your chatbots/human employees to adjust their conversation accordingly.
  • Why is Sentiment Analysis and Tone Analysis needed?
    Huge volumes of raw and unstructured business data are obtained daily, via customer feedback emails, help and support tickets, customer service chats, social media comments/conversations, surveys, etc. It is humanly not possible to capture and analyze all this information in a timely and efficient manner. Doesn’t help that 90% of the world’s data is unstructured and unorganized! There’s just too much business data to be processed manually. Sentiment analysis can create an efficient and cost-effective way to deal with all this data. For instance, critical issues can be identified in real-time- thereby avoiding a PR crisis.
    Additionally, since interpreting a sentiment is highly subjective and influenced by personal experiences, thoughts, and beliefs- multiple human employees may have different views on this subject. This may not always work in the favour of your business. Instead, a centralized sentiment analysis system, which has been trained on various aspects of analysis and that learns as it comes across various scenarios, will be beneficial to appropriately identify the nature of feedback and assist in timely damage control.
Types of Sentiment/Tone Analysis

There are different types of sentiment analysis models. Namely:

#1 Polarity Based Model

This model classifies feedback into 3 types- positive, negative and neutral. Let’s look at a few examples of the same:
I love how my Sony headphones function!
Classified as positive feedback
I still need time to operate my Sony headphones, but will update you soon!
Classified as neutral feedback
My Sony headphones battery keeps draining out after every 2 hours
Classified as negative feedback

#2 Emotion Based Model

This model looks at expressions like angry, happy, sad, etc. to determine the nature of customer feedback. Words like ‘anger’, ‘sad’ and ‘worry’ are associated with negative feedback, while words like ‘happy’, ‘like’ and ‘love’ are linked with the positive feedback.
Let’s look at a few examples of the same:
I am very happy with my new iPhone
Classified as positive feedback
I am very worried about my order delivery. Any idea when it will reach me?
Classified as negative feedback

#3 Urgency Based Models

This model is trained to identify the urgency in consumer queries.
Let’s look at a few examples of the same:
I need to speak to customer service ASAP!
My order has passed the delivery due date and it has not yet reached me.

#4 Intention Based Models

These models help customer service executives understand how interested a consumer is in a particular product/service/offer
Let’s look at a few examples of the same:
I am not interested in your new car insurance policy
Classified as Not Interested
Can you tell me a bit more about your new products? I am interested in buying some but Classified as Interested

#5 Emoji Interpretation

Let’s face it. It is much easier to communicate in emojis rather than typing out long sentences. Most of the Millennials use emojis to communicate their sentiments. It’s fast and gets the emotion through without sending lengthy paragraphs about the same.
Let’s look at an example that means the same whether in text or emoji/special character format:
I love the new MacBook
I 🧡 the new MacBook
The two sentences above have the same meaning. This particular sentiment model is trained to look out for special characters and symbols that interpret the same meaning as written sentences.
Business Benefits of Sentiment and Tone Analysis

#1 Social Media Monitoring

Social media gives consumers the ability to leave feedback on multiple channels (example- Facebook, Instagram, Twitter, etc.) These comments are public and can be viewed by anyone using the platform. In majority cases, the comments can influence other people’s buying choices. With more than 500 million+ Tweets and Facebook comments written daily, social media monitoring is a huge tasks and can be easily achieved by an AI powered tool.
Businesses can easily gain real time insights about how customers feel about their products and services by monitoring multiple social media platforms at once. This helps in Root Cause Analysis (RCA) of what went wrong and also helps human employees get in touch with aggrieved customers before the issue spirals out of control. This also creates a positive image for the brand- if issues are resolved in the nick of time.

#2 Better Customer Service

Outstanding customer experiences means a recurring and long term customer relationship. Sentiment and tone analysis can help companies respond with immediate, intuitive and personally crafted resolutions to people’s opinions and preferences. Queries can be automatically organized by topic and urgency to route them to the correct department and ensure that the most urgent issues are handled right away.
Additionally, you can also monitor if your employees are following appropriate protocol while addressing customer queries. Employee and customer conversations can then be used as the guideline to improve service quality, provide better training to customer service executives, improved future product development and much more!

#3 Improve Media Perceptions

Any misinterpretation of facts or negative connotation of a company’s products can lead to a negative perception amongst readers. Sentiment and tone analysis can track the understanding of the journalists, writers, market analysts, media researchers or independent contributors towards the company’s products and services. In case of any misunderstandings or wrong information provided to the readers, the PR team can reach out to these professionals and sort out the issue in time.

#4 Real Time Crisis Management

One of the main purposes of sentiment and tone analysis is prevention of any escalating complaint, which means that the crisis management team has to be on their toes. A single human employee cannot pay attention to multiple customer queries at once. This may cause frustration amongst your audience leading to escalations and public posts about the same. Timely preventive actions are of utmost importance, as it helps to eradicate online communication crises that usually spread all over the Internet in minutes. This requires frequent monitoring of the customers’ responses or opinions or any negative thread or comments online so that potential issues can be dealt with early before escalation.

#5 Discover industry leaders and influencers

By monitoring certain positive keywords or phrases your business can discover influencers that can help boost your business to another level through social media marketing.
Along the same lines, monitoring the kind of feedback the influencer obtains from their audience online will also help you shortlist a suitable candidate for your business.

Final Thoughts

Sentiment and tone analysis are a great help in assisting organizations to understand what their customers feel about their brand and thereby acting on the feedback. This also makes customers feel “heard”, thereby fostering long term brand relationships.
These models offer valuable insights for marketers to research and produce strategic solutions for customer issues or crises. This avoids the need for human employees to guess or make assumptions with inadequately sourced data. With the ever increasing amount of data being generated all over the globe, sentiment and tone analysis is the best tool for gaining critical insight into various data and automating processes.

We at FargoWiz can guide you properly in this field to understand your customers better. This will eventually help you achieve optimum business results.

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