Globally, the speech analytics industry is expected to be worth $3.8 billion by 2025.
A sizable portion of this comprises contact centre use cases, where the technology can be used to analyse call records, set up automated processes, and find out key insights into customer emotion without manually listening in on every call. According to a recent contact centre survey, speech analytics is fast becoming a “must-have” technology that unlocks key efficiencies without any outsized risk (e.g., uprooting existing tech, cultural shift, etc.). In fact, just 2% of respondents on the survey said they were unable to achieve efficiencies after speech analytics implementation.
For the remaining 98%, there are several ways to leverage speech analytics to make contact centres more efficient:
- Assist agents in real-time – Speech analytics can monitor ongoing calls to suggest timely recommendations – like mentioning a disclaimer if it was not said during the greeting, or alleviating customer frustration when negative sentiment is detected
- Predict customer intent – During the preliminary interaction with IVR, speech analytics can check for signs of customer intent and match the interaction with the appropriate agent. This cuts down agent preparation time and equips them to handle the call more effectively
- Escalate before it is too late – When negative sentiment approaches a predetermined threshold, speech analytics can automatically trigger the escalation workflow and involve a supervisor. To achieve this, you might need to connect speech tech with RPA
- Improve self-service – Responsive self-service can dramatically reduce call volumes, improving service levels and the quality of each interaction. Voice-based customer service assistants use NLP to understand queries and solve them, routing to a live agent only when necessary
- Train agents using speech analytics data – Information such as script deviation, missing out specific compliance keywords or phrases, impolite tone-of-voice, etc., is captured using speech analytics. This serves as an excellent baseline for training agents and improving performance
- Automate post-call activities where possible – Cumbersome post-call tasks like transcription and data entry can take up an inordinate portion of your agent’s workday. Leverage speech analytics to automate call transcription and summarisation, using RPA bots for routine data entry
- Earn revenues from cross-selling/upselling – Speech analytics can highlight high intent words and phrases such as “I wish” or “looking for” in real-time, alerting agents to cross-selling and up-selling opportunities. This can significantly improve your contact centre’s profitability
- Strengthen QA to avoid non-compliance – This is among the top use cases for speech analytics. Make sure that agents comply with regulations like PCI-DSS, HIPAA, GDPR, etc. by adhering to the right call script, to avoid heavy penalties layer on
Once you implement speech analytics in your contact centre, it is vital to measure the appropriate KPIs, to ensure that you reach the business outcomes originally intended. Some of the measurement indices to watch include:
- Increased FTR due to better training
- Optimised call volumes during peak periods and shorter queues
- Reduction in net cost per call
- Less frequent disputes and problem callers
- Higher CSAT from better customer intent analysis
