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Sentiment Analysis Helps To Gain Efficiency In User Service

Sentiment Analysis Helps To Gain Efficiency In User Service
  09/07/2019 08:07

The arrival of speech analytics to the call center, more than a decade ago, opened a new panorama of operational information in terms of understanding what users said. Well-trained data analysts were able to turn key words and phrases into useful intelligence for users and businesses.

Voice analysis also opened the door to obtaining data for customer service, through the recording of user conversations with agents in the contact centers.

With access to all these new data, it seemed that organizations already had the necessary information to decipher the entire user experience. However, solutions such as speech analysis work to tell us what users are talking about, but they do not tell us how they feel. Sentiment analysis guides call center data analysts towards what to do with that information.

With advances in natural language processing (NLP), combined with innovations in speech analysis, the next logical step for the analysis of feeling was the spoken word, as in contacts and conversations with users. The contact centers are adopting speech analysis as a tool for extracting data in recorded conversations.

Why Does The Sentiment Analysis Help To Gain Efficiency In Customer Service?

Sentiment analysis provides a better understanding of user calls, which can be used by supervisors, managers and others throughout the company. While speech analysis requires the skills of a data analyst, the analysis of feelings is an automated process that does not require human intervention.

Sentiment analysis, also known as opinion mining, consists of the process of determining the emotional tone behind a series of words, and is used to try to understand the attitudes, opinions and emotions expressed in an online mention.

Along with the provision of business intelligence with respect to the user experience, the sentiment analysis can also be implemented to improve the employee experience and monitor its performance. As with communications with users, you can provide automated feeling scores for agents, teams, groups, etc. The ratings of employee sentiments can be correlated with other key performance indicators (KPIs), which guide call center leaders to low-performing and high-performing agents.

With its focus on both the user experience and the employee experience, sentiment analysis is one of the call center solutions that has universal appeal for the market.

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