Over the last ten years, you’ve probably heard sentiment analysis mentioned by other telecom companies and providers – especially when discussing how to improve customer service. But what exactly is it? How can it improve customer service? And what does it have to do with VoIP? We’re here to answer those questions! Not only that but we’re also going to show you some key benefits sentiment analysis provides in your business communication.
What is Sentiment Analysis?
Sentiment analysis is a combination of natural language processing (NLP) and machine learning algorithms that allow machines to detect if a written or spoken interaction is positive, negative, or neutral. It does this by analyzing spoken and written dialogues, pauses in conversation, and even tone of voice. You’ve probably witnessed sentiment analysis without realizing it when using search engines, translation software, grammar correction programs, and even social media.
How Does Sentiment Analysis Work?
Sentiment analysis systems – typically implemented by APIs – fall into three major categories: rule-based, automatic, and hybrid.
Rule-based systems automatically analyze an interaction’s tone based on a set of rules the user has set beforehand. For example, a user makes a list of positive and negative words (bad, worst, wonderful, best, etc.) for the system to recognize. The system counts the number of those keywords that appear in a conversation. If negative words outweigh the positive words, the system will convey a positive outlook and vice versa. A neutral outlook is achieved when the amount of positive and negative words in a sentence are equal. This system is rather basic and would require regular fine-tuning to make sure your system is returning the right sentiment.
Automatic systems rely on the machine’s ability to learn, letting its knowledge evolve organically. Without getting into the nitty gritty details, these systems are fed text, that’s run through a computational linguistic process and returned as a category (positive, negative, or neutral).
Hybrid systems offer a mix of both automated and rule-based options. Of all the options, hybrid ones are usually more accurate in their sentiment analysis.
Business Use Cases for Sentiment Analysis
Now that you’ve got a better understanding of what it is – how can it help you and your business? The possibilities are honestly endless, no matter what your industry may be. Below are three of the most common uses for sentiment analysis:
Social Media & Brand Monitoring
Sentiment analysis allows you to gain insights into how customers really feel about your business – from Twitter mentions and Facebook posts to blog posts and online forums. While you may already be monitoring the number of mentions, you probably don’t have a window into the quality of those mentions. This technology also allows you to categorize these conversations and brand mentions and send them to the proper department.
Customer Service
We all know that your product may be excellent, but if your customer service isn’t your brand and your bottom line will suffer. Your customers expect quick and personalized service and aren’t afraid to switch brands to get it. In fact, according to a recent study, one in three customers will leave a business after just one bad experience.
This is where sentiment analysis can come in handy. It can analyze support tickets, chats, and calls, sort them by topic and urgency and send them to the right agent or department. This means the most urgent requests get handled immediately rather than waiting at the end of a very long line. Implementing sentiment analysis will help increase efficiency and decrease churn rates, keeping your customers happy and your service representatives at peak performance.
Market Research
Sentiment analysis enables your marketing team to tap into information more deeply than before. They can analyze online reviews and compare them to the competition or discover emerging markets by applying sentiment analysis to market reports or business journals. Being able to turn qualitative data into qualitative data is a highly valuable resource for any marketing professional. And they’ll be able to with sentiment analysis!
How Can I Apply Sentiment Analysis To My Business Communications?
The answer’s simple: do it yourself or invest in a sentiment analysis tool. For most businesses, doing it themselves is far too time-consuming. After all, it would require a team of data engineers, loads of time, and a significant initial investment. On the flip side, engaging with a sentiment analysis provider allows you to implement the service immediately, without knowing how to code, and even integrate the service to multiple applications.
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