How companies can leverage sentiment analysis to improve operations and maximize their workflows

2021/ 03/06

Sentiment analysis is a technique that integrates natural language processing and machine learning, and is usually used to analyze customers' opinions, moods, and speaking styles. By the application of the technique, companies can gauge the emotional state of the clients, by which a program can understand whether there is a positive, negative or neutral emotion behind a text. These information are useful and essential in several business applications, which you can read about in more details below.

 

How does sentiment analysis work?

Human speech and language are all really complex systems, and due to their subjective interpretation, they are difficult to measure or quantify, so speech recognition and sentiment analysis are also complex. While some things are clearly recognizable in face-to-face communication or in a phone call conversation, such as basic emotions, it is a very difficult task to make these signs understandable for a machine through measurements and quantifications.

There are several kinds of sentiment analysis software programs, some of them are only text based. These usually work by scoring words, and from the sum of the points, the programs can tell whether a text is emotionally positive or negative. Besides these, there are more sophisticated, voice-based software programs which are noticeably more accurate than the text based method. These voice-based programs, besides using the scoring system, analyze the rate of speech, voice inflections and also stress signals and the level of stress in the customers’ voice. In addition, modern speech recognition programs, such as the Alrite of Régens, automatically generate a searchable transcript, in which words can be categorized. Applying sentiment analyses to these systems make it even easier to identify a common issue or feedback.

The word scoring algorithm can relatively accurately determine the mood of the speaker by observing the text of dialogues, but for example for recognizing sarcasm, the tone of the voice must be taken into consideration. For more accurate conclusions, it is also worth monitoring a costumer’s frustrations, as well as the signs of stress. Taking all this into account, the emotional state of the speaker can be determined extremely well.

What can sentiment analysis be used for?

Brand monitoring and building

Businesses can benefit a lot from being able to track their audience and their reactions, and sentiment analysis software programs offer a good solution for that, because with them, a business can also monitor its own reputation. Added to this, it enables companies to identify its peaks and valleys in the history of the brand, and from the summarized reactions and feedback, they can improve the brand and their services.

For the success of businesses, it is usually essential that the opinions, feedback and customer needs are taken into account, so that the brand can adapt to them. Through the eyes of a satisfied or dissatisfied customer, managers can gain insight into the effectiveness of their services, and can see which parts should be improved. These can be used to conform the image of a company or brand to its audience, or just making a simple change in the structure of a call center or website can improve customer satisfaction.

Call center supervision

Sentiment analyzers are often applied in call centers to help the agents or automated systems to see why and in what emotional state customers are calling, to be able to provide them the most appropriate help and guidance. However, customer reviews and reactions can also reveal useful information about customer service agents, giving managers insight into call centers. Based on customer reactions, employees can be developed and trained, in order to optimize the efficiency of the given work area.

Campaign tracking

It is also essential to monitor the feelings, opinions and reactions of a mass of people during political campaigns, and sentiment analysis can be perfectly applied for these purposes. For instance, during the 2016 U.S. election, posts on Twitter were analyzed, and the campaigns adapted to the current public mood, so that they could make the right move at the right moment, increasing the popularity of the campaign.

Marketing and product design

To give you an example, Apple and KFC both apply sentiment analysis in their marketing, based on public comments and reviews from the users of the Internet. With that, KFC uses pop cultural icons and even popular memes in its ads, while Apple gathers criticism of its rivals and sharpens its ads based on them and the differences.

Google and TripAdvisor also rely on customer feedback, for instance, they develop websites and user interfaces to create a platform that satisfies the forever changing needs of their audience.

If you would like to summarize and track your customers’ feelings and reactions during a phone call, for example, sentiment analysis integrated speech recognition software programs can offer you a great solution. The Alrite speech recognizer of Régens is about to be completed by sentiment analysis, which will certainly provide new opportunities in business implementation.

Source: Synaptiq, CallMiner, VoiceBase

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