Speech analytics technology can be leveraged to help better understand friction in the customer journey and improve customer retention. Examples of speech analytics include word clouds, transcription, and sentiment analysis.
Data is everywhere. It informs decision-making, recognizes critical trends, and increases the overall quality of patient care. However, collected data is often unstructured or not easily accessible. It’s estimated that upwards of 90% of data is unstructured according to Forbes. Speech analytics can bring value to an organization by analyzing data, gaining context, and drawing actionable meaning.
What is speech analytics?
“This call may be monitored and recorded for quality assurance” is a familiar line many customers hear. Speech analytics (or Natural Language Understanding) is becoming a more standard tool that leverages artificial intelligence to analyze recorded conversations for an organization. It highlights words and phrases most used by callers to identify themes and trends.
The global speech analytics market is expanding rapidly, especially in the healthcare industry. The market is predicted to be worth $4.5 billion by 2026, a 20.5% increase from 2021. While the global healthcare AI market is expected to expand to $194 billion by 2030 (from an estimated $8.2 billion generated in 2020). Speech analytics technology can be leveraged to help better understand friction in the customer journey and improve customer retention.
Examples of speech analytics include word clouds, transcription, and sentiment analysis. These tools show what is top of mind for a caller, like billing, benefits, digital accessibility, and so on. However, these insights are not always actionable because the context is usually missing. Organizations are missing ‘why’ these words and phrases are top of mind. A word cloud may show a customer is frustrated, but what are they feeling frustrated about? Meaningful change can only happen if context is applied to data.
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