Implementation of Speech Analytics

The implementation of speech analytics is not as simple as installing software. It requires a team of experts, backed by sound business knowledge, to drive the process

There are four main stages in the implementation — Call Injection, Fine-Tuning, and Discovery

Call Injection involves feeding conversations from source systems such as call recorders into the speech engine. The associated metadata — agent’s name, customer’s basic information, day/timestamp — is also fed into the engine.

 The speech engine converts audio (including acoustic signals such as agitation or noise) into the text using speech recognition. You can also know more about Call Center Speech Analytics or Voice Analytics by visiting

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Fine-Tuning is an ongoing process that involves building specific call categories in the call library by identifying relevant keywords or phrases.

Once the call categories are created, fine-tuning is conducted to ensure that the tool correctly segregates calls based on defined categories. Sample calls are analyzed manually and validated against the analytical tool’s findings.

Discovery involves the system automatically analyzing customer interactions and assigning them to pre-defined categories. Key metrics are used to measure various performance indicators such as agent quality, customer satisfaction, emotion, and first contact resolution.

The insights derived from this stage are used to create actionable reports for relevant teams. The minutest details require attention during the implementation. The team should also proactively analyze and fine-tune the speech analytics process on a periodic basis

Speech analytics solutions need to customize. Moreover, they need to be continually fine-tuned to meet evolving business needs.