Sentiment Analysis in business, also known as opinion mining is a process of identifying and cataloging a piece of text according to the tone conveyed by it. This text can be tweets, comments, feedback, and even random rants with positive, negative and neutral sentiments associated with them. Every business needs to implement automated sentiment analysis. If you doubt it, here’s a little perspective. The accuracy can never be 100%. And of course, a machine does not understand sarcasm. However, according to a research, people do not agree 80% of the time. It means that even if the machine accuracy does not score a perfect 10, it will still be more accurate than human analysis. Also, when the corpus is huge, manually analyzing is not an option. Hence, sentiment analysis in business is more than just a trend.
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Sentiment Analysis in business, also known as opinion mining is a process of identifying and cataloging a piece of text according to the tone conveyed by it. This text can be tweets, comments, feedback, and even random rants with positive, negative and neutral sentiments associated with them. Every business needs to implement automated sentiment analysis. If you doubt it, here’s a little perspective. The accuracy can never be 100%. And of course, a machine does not understand sarcasm. However, according to a research, people do not agree 80% of the time. It means that even if the machine accuracy does not score a perfect 10, it will still be more accurate than human analysis. Also, when the corpus is huge, manually analyzing is not an option. Hence, sentiment analysis in business is more than just a trend.
The Role of Sentiment Analysis in Business:
The applications of sentiment analysis in business cannot be overlooked. Sentiment analysis in business can prove a major breakthrough for the complete brand revitalization. The key to running a successful business with the sentiments data is the ability to exploit the unstructured data for actionable insights. Machine learning models, which largely depend on the manually created features before classification, have served this purpose fine for the past few years. However, deep learning is a better choice as it:
Automatically extracts the relevant features.
Helps to scrape off the redundant features.
Rules out the efforts of manually crafting the features.
At ParallelDots, we have powerful sentiment analysis API that uses deep learning which provides an accurate analysis of the overall sentiment of the given text.
What follows now is how businesses can leverage the sentiment analysis data:
Sentiment Analysis in Business Intelligence Buildup:
Having insights-rich information eliminates the guesswork and execution of timely decisions. With the sentiment data about your established and the new products, it’s easier to estimate your customer retention rate. Based on the reviews generated through sentiment analysis in business, you can always adjust to the present market situation and satisfy your customers in a better way. Overall, you can make immediate decisions with automated insights. Business intelligence is all about staying dynamic throughout. Having the sentiments data gives you that liberty. If you develop a big idea, you can test it before bringing life to it. This is known as concept testing. Whether it is a new product, campaign or a new logo, just put it to concept testing and analyze the sentiments attached to it.
Sentiment Analysis in Business for Competitive Advantage:
If you are truly catching up with the applications of sentiment analysis in business, you should be open to experimenting with it tactfully. Like I mentioned before, sentiment analysis can be performed on any piece of text. So, why just settle for applying it to your brand? Getting x% negative or positive reviews on a certain product doesn’t make much sense if you don’t have a y% metric to compare it with. Knowing the sentiment data of your competitors gives you the opportunity as well as the incentive to perk up your performance. Sentiment analysis in businesses can be very helpful in predicting the customer trends. Once you get acquainted with the current customer trends, strategies can easily be developed to capitalize on them. And eventually, gain a leading edge in the competition.
Enhancing the Customer Experience through Sentiment Analysis in Business:
A business breathes on the gratification of its customers. The experience of the customers can either be positive, negative or neutral. Owing to the internet savvy era, this experience becomes the text of their social posting and online feedback. The tone and temperament of this data can be detected and then categorized according to the sentiments attached. This helps to know what is being properly implemented with regards to products, services and customer support and what needs improvement.
Getting a positive response to your product is not always enough. The customer support system of your company should always be impeccable no matter how phenomenal your services are.
48 hours locked out ofandhas still not responded. This is very disappointing.
— Chase Lepard (@chaselepard)
Sentiment Analysis in Business for Brand Brisking:
A brand is not defined by the product it manufactures or the services it provides. The name and fame that build a brand majorly depend on their online marketing, social campaigning, content marketing and customer support services. Sentiment analysis in business helps in quantifying the perception of the present and the potential customers regarding all these factors. Keeping the negative sentiments in knowledge, you can develop more appealing branding techniques and marketing strategies to switch from torpid to terrific brand status. Sentiment analysis in business can majorly help you to make a quick transition.
The applications of sentiment analysis in business are plenty and overwhelming. Gaining a greater business value with sentiment analysis depends on what tool you use and how well you use it to your advantage.
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