Lifting all boats: Using AI to replicate your top-performing agents.

In traditional contact centres, identifying why the top 5% of agents consistently outperform the rest has always been a source of frustration for contact centre leaders.

By Greg Jarvis, Global Customer Success Director at Connect

Managers know the top-performing agents intuitively understand the customer journey, and can weave compelling narratives, picking up on subtle audio cues while balancing soft interpersonal skills with hard-sell tactics.

However, they have struggled to define or systematically replicate their success across the remaining 95% of the workforce.

The capacity constraints.

The root cause typically stems from a lack of visibility into the qualitative narrative of the most successful interactions.

Traditional Quality Assurance (QA) and Quality Management (QM) processes rely on manual reviews that typically sample less than 5% of total voice interactions at best.

Under this legacy model, QA analysts focus heavily on compliance checklists and customer experience etiquette, while team leaders scan calls for immediate upsell signals.

Neither group has the time to listen to an entire 40-minute call, let alone spot the microscopic linguistic and behavioural nuances that separate an average agent from an extraordinary one.

Furthermore, because manual QA naturally targets new joiners or underperforming staff, contact centres regularly miss the critical learning opportunities hidden within their best performers' conversations.

The unstructured data problem.

When contact centre leaders attempt to diagnose performance, they instinctively turn to a familiar matrix of structured operational metrics: Cost to Serve, Average Handling Time (AHT), First Call Resolution (FCR) and queue volumes.

But structured data only forms the outer border of a jigsaw puzzle – it tells you what is happening, not why. To complete the picture, organisations must systematically analyse unstructured interaction data sourced from voice recordings, chat transcripts, and email threads.

By converting unstructured interactions into structured, analysable data using speech-to-text transcription and Natural Language Processing (NLP), Natural Language Understanding classifies every conversation by intent, tone, sentiment, and customer effort.

When driven by AI, this analysis shifts QA coverage from a 5% sample to 100% of all interactions across every channel.

Decoding high-performing agent interactions.

When automated Data-Driven Insights (DDI) examine 100% of conversations, machine learning models isolate the exact root-cause behaviours that drive successful outcomes.

Instead of relying on subjective agent surveys or rigid script checklists, AI surfaces the true mechanics of high-value engagements.

For example, while average agents focus exclusively on commercial features, top performers intuitively introduce human elements, reassuring customers on claim payout timelines or beneficiary care before steering back to the product details.

The AI-led DDI analysis can also identify the precise sequence of the selling journey, highlighting how top agents master the narrative order to deploy soft empathy or firm closing cues when most relevant.

Furthermore, automated tone analysis reveals how elite agents detect subtle shifts in customer sentiment, prompting them to adapt their pitch or address unspoken hesitations.

Once these empirical insights are identified, contact centre leaders can take top agents off the line to validate the findings, shaping raw data into a practical, customer-friendly training framework.

Lifting all boats by replicating excellence at scale.

The true commercial value of AI is not found in replacing staff, but in elevating the performance of your median workforce.

Taking average journeymen agents and improving their effectiveness by 10% to 15% delivers a massive uplift in operational performance, which far outstrips expensive, generalised sales training programs that rarely yield a clear ROI.

• Agent assist: Micro and Small Language Models analyse live call transcripts in real time, feeding immediate prompts, sentiment alerts, or relevant cross-sell options directly to the agent's screen based on the customer's real-time tone and intent.
• Structured scripting: The narrative structures of top performers are embedded into core conversational workflows, giving average agents a proven roadmap for leading complex calls.

Proving the value of AI.

By expanding visibility to 100% of customer interactions, AI-driven DDI bridges the gap between frontline execution and strategic management. Supervisors are freed from the administrative burden of manual call scoring, allowing them to focus their time on targeted, data-backed coaching.

Meanwhile, CX leaders gain real-time operational intelligence to streamline broken processes, reduce AHT, and improve FCR to elevate Customer Satisfaction (C-Sat) scores across the entire enterprise.

At Connect, we help contact centres move beyond lagging metrics and manual blind spots. By unlocking the unstructured data hidden within every call with our DDI service, we enable leaders to turn outlier success into an operational standard, proving the true commercial ROI of AI-led transformation.