From Community Insight to Operational Control

Coffee with Callbi has grown well beyond the webinar format into a practitioner-led community of Callbi users, operational leaders, and CX professionals who share a common goal: using conversation analytics to address real issues in live contact centre environments. Each session connects people actively using Callbi across quality assurance, operations, compliance, and coaching, creating a forum based on experience rather than theory.

Unlike traditional vendor briefings or product demonstrations, Coffee with Callbi is intentionally conversational and peer-led. The focus is on practical insights, honest discussions, and shared learning among organisations facing similar operational challenges. Participants include QA leaders, operations managers, solution architects, and CX strategists, all offering perspectives shaped by daily use of analytics rather than abstract theories.

This community aspect is fundamental to the value of Coffee with Callbi. As the user base expands, so does the collective knowledge of the group. Each session builds upon previous discussions, allowing themes to be revisited, challenged, and refined. Topics such as silent time, AHT optimisation, QA productivity, agent trust, sentiment analysis, and adoption are explored not as isolated concepts but as interconnected elements of operational control.

The session summarised in this paper reflects maturity. The discussion focused not on what speech analytics can do, but on how it is practically utilised, where it provides the most immediate value, and why some approaches succeed while others stall.

From Recording Conversations to Managing Performance

Rod Jones started the discussion by questioning a long-standing industry belief. Most contact centres record calls, but few use those recordings as their main source of operational data to manage performance. Recording, transcription, and dashboards alone do not lead to improvements. What truly counts is recognising the operational signals within conversations and acting on them consistently.

Rod positioned analytics as a management discipline rather than a technology deployment. When used as an operational tool, speech and text analytics directly support quality assurance, coaching, compliance oversight, workforce planning, and service consistency. When used solely as a reporting layer, they risk becoming underutilised and mistrusted by the very teams expected to act on the insights.

Silent Time as a High-Leverage Signal

One of the most detailed and practically valuable parts of the discussion centred on silent time, a metric often overlooked or underestimated. Henriette Potgieter explained why silence should be regarded as a leading indicator rather than a secondary metric. From an operational perspective, silent time signifies paid labour that does not generate customer value and often points to deeper issues such as system latency, process friction, or agent uncertainty.

Henriette explained that when silent time is surfaced, trended, and segmented at scale, it becomes a diagnostic tool. It allows managers to distinguish between behavioural issues and structural constraints, enabling targeted intervention. Importantly, she emphasised that silence is not about blame. It is about understanding where the operating environment makes it more difficult for agents to perform.

Nosihle Mbatha emphasised this with frontline operational insight. In collections environments, silent time often acts as an early warning of system complexity or loss of confidence. Tackling it usually leads to secondary improvements in wrap-up discipline, call flow, and overall call hygiene, with measurable effects on both efficiency and outcomes.

Rethinking AHT Without Undermining Value

The discussion then shifted to Average Handling Time, with a clear warning against its past misuse. Henriette was explicit that AHT should never be reduced arbitrarily. The aim is not to cut down meaningful conversation, but to eliminate waste. Analytics allows AHT to be broken into its parts, separating value-adding talk from avoidable dead air and unnecessary delays.

The panel agreed that even modest, intelligent reductions provide tangible planning and capacity benefits when implemented consistently at scale. This precision shifts AHT from a blunt performance tool into a controlled optimisation lever.

Quality Assurance at Scale

A key theme throughout the session was the shift of QA from sampling to systemic insight. Natasja Bowes, Head of Quality Assurance and Training at Lumen and LGR, offered one of the most tangible practitioner perspectives.

Natasja explained how analytics fundamentally change the nature of QA work. Traditional models limit analysts to a set number of audits each day, leading to anecdotal results. With analytics, QA teams focus on recognising patterns across large volumes of interactions, greatly increasing coverage and improving consistency. The emphasis shifts from individual failures to opportunities for systemic improvement. Page | 3

This shift has a direct impact on coaching. When feedback is grounded in trends drawn from all interactions, coaching conversations become evidence-based and less confrontational. Natasja linked this directly to improved agent acceptance, stronger engagement, and reduced attrition, particularly in high-pressure environments.

Trust, Fairness, and Agent Acceptance

Nosihle elaborated on the human aspect of adopting analytics. She discussed the long-standing mistrust many agents have towards QA, often caused by perceptions of bias or selective call-picking. When implemented transparently, analytics can alter this dynamic.

Replacing selective sampling with objective trend analysis helps organisations remove the feeling of personal targeting. When agents realise that insights are used to enhance systems and skills rather than just to spot faults, trust grows. This trust is essential for effective coaching and ongoing performance improvement.

Turning Insight into Action

The realisation of analytics was further strengthened by Anton Pretorius, Senior Solutions Architect at iSON Xperiences. Anton grounded the discussion in the realities of multi-client, high-volume environments. He emphasised that analytics only delivers value when it is embedded into daily workflows rather than layered on after the fact.

Speed to insight, configurability, and ease of use were emphasised as key factors in adoption. If insight is slow, overly complex, or hard to interpret, it will not be acted upon. Anton highlighted the importance of starting with a small number of high-impact measures, delivering early wins, and expanding gradually to build confidence and momentum.

Product Insight and Practical Enablement

Corey Springett played a crucial role in translating operational goals into practical implementation guidance. Corey warned against over-engineering the starting point, endorsing a start-small, act-fast approach. Deploying a limited set of meaningful queries, publishing dashboards early, and refining iteratively accelerate time-to-value and foster engagement.

Corey also discussed sentiment analysis, warning about opaque AI scoring. Although AI summaries provide valuable context, he advised using targeted text queries to reliably identify negative sentiment, escalation risk, regulatory references, and abusive language. This helps operational teams maintain control over what is measured and the reasons for it.

Henriette emphasised the importance of enablement, highlighting structured training, intuitive in-platform guidance, and contextual help as vital for adoption. The focus was on developing internal capability rather than reliance on specialists.

Concluding Perspective

This Coffee with Callbi session showed that analytics maturity is not determined by technological sophistication but by disciplined application. Organisations that thrive see conversations as strategic assets and consider analytics a key management capability.

When insight is accessible, trusted, and integrated into daily practice, the results are tangible. Less waste, higher QA productivity, fairer performance management, improved agent engagement, and more confident leadership decisions. Analytics shifts from being just a reporting tool to a driver of operational control and sustainable performance.