If there is a need to scan through a lot of surveys for positive or negative messages, it can be automated using sentiment analysis AI. To learn how it works, the way it is designed, and what applications it has in the field of business, check out the information down below!
What is Sentiment Analysis?
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Put simply, sentiment analysis is what AI uses to study information for subjective information such as a positive, negative, or neutral response. The material can include social media platforms, reviews, surveys, and so on. For business owners especially, this could be a very powerful tool to know how their brand is perceived by the public.
How does Sentiment Analysis Work with AI?
The concept is quite simple – using machine learning and natural language processing, the AI will translate the material in question into an algorithm it can understand, and thus a choice can be made based on that. Then, one of three results will show up, with percentages included: positive, negative, or neutral.
First comes natural language processing. This process allows the AI to understand the human language through various means, as it analyses the text and gives semantic meaning to the words, archiving them. This helps to make sense of the words and the text and works for recognizing human speech.
Then, the machine learning process takes place. By seeing the patterns and algorithms, the AI automatically improves itself. If there is an inaccuracy in its code, it is programmed to learn from it and fix it, so that in the future it can be more and more precise. In a way, this is how the machine keeps growing just by itself.
Both natural language processing and machine learning, when put together, create a valuable option for sentiment analysis. This makes an AI more accurate the more text it reads along with delivering an almost perfect decision on whether the material is positive, negative, or neutral. As it has more practice, the accuracy may also improve.
What Can Customer Sentiment Analysis Be Used for?
Taking sentiment analysis and combining it with customer feedback is a fast way to find out the results of surveys, reviews, social media comments, analyzing trends, and so much more. It has almost limitless capabilities, and any business can benefit from it. As an example, it is a great tool to use for a business to compare itself with a competitor, see the advantages and disadvantages, and thus know what to improve on.
Which Application of AI is Used for Customer Sentiment Analysis?
There is a number of AI customer sentiment analysis applications that can be used to have, among which is a service by InData Labs. Simply fill in the blank form with information about the company and write about how the service can be of help. Another useful tool is MoneyLearn’s No-Code Text Analytics, which also has a free demo that can be downloaded.
What are the Areas Where Sentiment Analysis Can Be Applied?
Since AI-based sentiment analysis is very effective and can be applied to almost any business for success, especially considering that it is all about analyzing data – instead of having a person do it, this option can save a lot of valuable time. Down below, a list of what business fields sentiment analysis AI can be applied to can be found, along with a description of the impact that it can have.
Predictive Analysis
Sentiment analysis is surprisingly effective at predicting how the situation of a business will unfold in the future by looking at its history records over the years. Predictive analysis is one of the most widely utilized machine learning techniques for assisting organizations in making thought-through decisions and navigating severe setbacks.
Customer Service
A satisfied customer is one who is likely to recommend the product to others. Simply asking the clients to rate the product in question is a way to enable sentiment analysis – and that way, the data can be categorized. After that, the information will help in correctly implementing much needed modifications that will make the business reach the next level.
Improving Products
Through the many various means of looking through surveys, reviews, and monitoring social media, a decision can be reached on how to improve your product or service. There will be a range of opinions, which will be sorted by sentiment analysis AI, so it will be clear what the user experience really is. Looking at the negative views, a concise conclusion on what to do to make the product better can be perfectly clear.
Stand Out Among the Competitors
By seeing who the competitors of your business are, their strengths and weaknesses can be found. Using sentiment analysis, take note of what they do right, and improve on what their customers seem to be complaining about – thus, reaching a better product overall. And of course, people would be attracted to a more trusted company and one with a better product.
Brand Monitoring
Analyzing the tone of comments made online about the business or product might help you notice any spikes in unsatisfactory views. Most crises may be avoided by responding quickly to dissatisfied customers. The context of your numerical statistics is understanding client sentiments. Sentiment analysis in real-time can assist in determining how the company is perceived and evolving.
Monitoring Social Media
Customers who openly discuss what they like and dislike about your product may be found on social media, which is the best place to look. Very valuable information may be gained about how various customers view your product or brand by tracking social media mentions of it. This kind of goes hand in hand with the idea of improving your product and taking customer experience into account.
Market Research
Sentiment analysis not only gives you information about the internet presence of a company but also lets you know what consumers in the target group think about your rivals. These deep insights benefit companies in achieving a sustainable competitive advantage by identifying the faults in products and services that target a specific market.
Advertising
What are the best algorithms for creating the most perfect advertisement that will capture a lot of customers? That can be found out through sentiment analysis, as the AI will grow and learn how to make the most attractive picture-perfect promotional material to get more publicity. And that is how it can be very effectively used for advertising purposes.
What is the Future of AI Sentiment Analysis?
In the future, as sentiment analysis technology is developed, even more, it is very likely to go beyond the idea of only recognizing positive, negative, and neutral responses. Emotions such as happiness, anger, and sadness – all of that are most likely to be interpreted in the coding. Interestingly, with this concept in mind, it is possible to push the AI to the limit of even recognizing depression signs in people just by reviewing their comments.
Very far into the future, it may also be possible to judge a person’s intent based on their writing. It would take into account the underlying context that may exist within a text, which would be quite hard to easily decipher even for humans. This, however, would help companies better predict what customers think of their products.
And in development already, is the concept of automatically putting the spoken words of a person into text and making a sentiment analysis at the same time. This would be especially useful during phone calls of clients with customer support, as the AI would mark the call as positive, negative, or neutral depending on how it ended.
Conclusion
Consumer sentiment analysis by Artificial Intelligence is a way for businesses to gather intel through reviewing texts, such as social media comments, surveys, reviews, and much more. It is a great way to make improvements to your business and find out the pros and cons of all the competitors, and thus bringing better products and attracting more customers due to better user experience.
As years go by, the world will see more development in the sphere of sentiment analysis, pushing limits to such an extent that it will be possible for AI to understand human emotions such as happiness, sadness, disappointment, inspiration, and many others. This could help the creation of actual humanoid AI, but that is probably far into the future. All in all, this is an extremely helpful breakthrough in technology that businesses throughout the world should pay attention to.
Author bio
I am Nikki Veillon, an enthusiast of all things related to technology, artificial intelligence, data, the future of the IT sphere, and most importantly, cats. Specifically, the development of AI is what I find intriguing, as it is a field of interest for me. I can be found and contacted at AI forums following this link.
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