Speech analytics is a software technology that transcribes 100% of voice calls and derives deep insights, trends, and metrics from each call. It utilizes AI services including transcription, natural language processing, and speech technologies to understand, analyze, and derive insights from a voice conversation. These insights are then used to evaluate agent performance, assess customer experience, and monitor organization-wide strengths and shortcomings on every voice interaction.
Data Processing: It uses a number of AI-services, including automatic speech recognition, transcription, and tonality-based sentiment analysis to analyze both the audio recording and call metadata.
Analysis: Once the call recordings are analyzed, speech analytics then categorizes, keyword spots, redacts (for compliance purposes), and reports its analysis of the call.
Insights: The speech analytics platform then delivers detailed reporting on the analysis, including call quality, sentiment, agent performance, and compliance monitoring.
Speech analytics benefits
Significantly increases call coverage: Historically, QA teams in call centers on average quality check 2-4 voice calls per agent, per month. With speech analytics, organizations can review up to 100% of voice calls.
Monitor key KPIs: Speech analytics empowers customer service and support teams to set up analysis on any number of customer interactions moments. This is anything from supervisor escalations and compliance violations, to customer satisfaction and average handle time (AHT).
Provide near-realtime speech analytics feedback: With faster analysis and 100% call coverage, supervisors can deliver tailored feedback almost immediately to agents.
Uncover hidden inefficiencies: By monitoring a variety of contact center KPIs, leadership can better understand what's impacting those KPIs and unearth inefficiencies causing them.
Personalized training: With deep insights on 100% of customer calls per agent, supervisors and L&D teams can create custom tailored coaching sessions for individual agents.
Improve customer experiences: With sentiment analysis, teams can look at the things driving positive customer experiences (eg. empathy statements), and indicators of negative ones (eg. supervisor escalations), and in turn, reduce customer churn.
Speech analytics use cases, examples, and KPIs
Monitor mandatory compliance dialogues
Regulatory compliance is paramount across all industries, most notably financial, insurance, and healthcare, ensuring the protection of customer data, backed by strict legislation to enforce it. As a result, monitoring mandatory compliance dialogues and categorizing voice calls relevant to specific compliance regulations is mission-critical.
The beginning of a conversation is important from both a customer experience and a compliance standpoint.
Did the agent positively greet the customer, introduce themselves, and get the customer’s name?
From there, did the agent successfully go through any customer verification required for compliance (eg. phone number, SSN, credit card information, etc) or any required dialogues (eg. “This line is recorded.”)
Mention company name
Recorded line message
The end of a conversation is also important for customer experience, and it also is an opportunity to both better confirm how the call went and create next steps.
Did the agent adhere to a call closure script?
Did they set a follow-up appointment when necessary, ask if the customer if they have any additional questions or issues before ending the call, or ask if the service they were provided was within their standards?
Thank customer for calling
Offer further assistance
Supervisor escalations are a strong indicator of a negative customer experience, a metric for agent call-handling, or an organizational inefficiency. Escalations in any contact center are costly due to the amount of time and resources required to resolve them.
Identify when customers are escalating calls to a supervisor/manager, and know not only who, but what is driving escalations.
At an agent level, see who the top outliers are. For why escalations are happening, review what behaviors and situations drive escalation rates, and data to quickly address it.
Training teams can course-correct agent behavior through education and awareness.
Monitor where negative experiences are occurring, and determine if they are people, process or product-related.
Make data-backed decisions to create coaching programs for agents, redesign processes, and deliver product feedback back to the organization.
Customer satisfaction (CSAT)
Customer negative sentiment
Hold time violation
Average speed of answer (ASA)
Gestures of Good Will (GOGW)
Operational efficiency is critical for improving critical contact center KPIs, all contributing to lowering average handle time (AHT).
Identify hold time violations, dead air, first call resolution and determine AHT.
Build comprehensive scorecards of efficiency KPIs to better train agents with more relevant coaching to improve performance.
Hold time violation
Average speed of answer (ASA)
Speech analytics in the contact center
Speech analytics has driven QM processes to grow more automated, more accurate, more efficient, and more relevant to the agents themselves. It’s had a massive benefit on organization leaders, supervisors, and the contact center agents themselves, impacting customer experience, compliance, and learning and development. A speech analytics solution drives:
More automation: Analysts no longer have to manually score calls. From transcription to analysis, the entire process is automated.