There is a popular saying, “The customer is always right”. Despite its literal meaning not always being true, what it actually means is that all requests, queries, and demands of customers must be tended to, if a company hopes to retain them and make consistent profit. In today’s times of intense competition, where fortunes can be made and destroyed in days, providing a satisfactory customer experience has become more important than ever. This is why an increasing number of companies are setting up customer support departments or outsourcing the task to contact centers.
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Thus, with the increasing number of contact centers, the speech analytics market is also prospering. Compared to $1,010.4 million in 2018, the sale of such software is expected to be worth $2,910.1 million in 2024, with the revenue increasing at a 19.9% CAGR during 2019–2024 (forecast period). As the term suggests, speech analytics software studies the speech on various parameters, such as volume and pitch, to determine the emotions of the speaker. Currently, among all applications of such software — call monitoring, agent performance monitoring, customer experience management, and risk and compliance management — it is mostly widely used for customer experience management.
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Speech analytics determines why the customer has called, their mood, and reactions to the products and services on offer. This helps customer support teams with pinpointing the areas where the team members need improvement, while interacting with customers, with a thorough knowledge of customers’ expectations and requirements. The better companies serve their customers, the more likely they are to retain them, which is why customer experience management has become an important focus area. As a result, even in the coming years, the use of speech analytics for this very purpose will grow the fastest.
The growing usage of this software is being mirrored by a shift of people from phonetic transcription to phonetic indexing. Compared to the former, the latter is easier, as it doesn’t require the scanning of a vast dictionary of words, which is also why it is faster than transcription. Speech analytics software working on the indexing method converts audible speech into a series of phonemes, following which it scours for just a predetermined words’ list. Therefore, with such solutions, a higher call volume can be analyzed without an increase in the number of servers.
