AI Reporting and Insights

 Most reporting tools track operational metrics like response time or queue volume, but stop there. Quiq combines that real-time operational reporting with AI-powered conversation analysis, so you get a single view of both how your systems are performing and what’s actually happening inside each conversation. That means you can see queue wait times and staffing needs alongside deeper analysis, like where an AI agent missed a resolution or where a knowledge gap caused an escalation. Because AI Analysts can reason across your business systems, insights don’t stop at a dashboard. They can automatically update CRM records, send manager alerts, or trigger workflows based on what they find, closing the loop between insight and action.

Every one. Traditional QA processes typically sample a small percentage of conversations, which means most interactions go unreviewed and problems can hide in the majority you never look at. Quiq’s AI Analysts score 100% of interactions across both AI and human agents, so you get full conversation coverage rather than an educated guess based on a sample. That full coverage makes it possible to identify knowledge gaps, missed resolutions, and escalation patterns across every channel, not just the ones you happened to spot-check. Panasonic used this kind of complete visibility to help drive a 75-point NPS improvement across its European customer service operations.

Yes. Rather than forcing you into predefined categories, Quiq lets you define what “good” looks like for your business, using your own criteria, categories, and taxonomy. You decide what counts as a low CSAT interaction, what “resolved” means for your workflows, and which behaviors matter most to score. This runs on every conversation, not just a sample, and works alongside standard metrics like CSAT, Average Handle Time, First Contact Resolution, and NPS, plus purpose-built measures like Quiq’s own Work Time metric. Because these custom metrics are generated by AI Analysts that can reason across your business systems, they don’t stop at reporting. They can flag churn risk, surface training needs, or trigger a workflow automatically when something crosses a threshold you define.

Both, in one place. Quiq analyzes conversations handled by AI agents, human agents, and the conversations that move between them, without losing context at the handoff. For human agents specifically, you can track response times, handle time, and CSAT by individual agent or team to spot coaching opportunities quickly. For queues and workforce planning, you get real-time visibility into volume, staffing, and saturation, down to 30-minute intervals. The unified view matters most at the handoff point: when a conversation transfers from AI to a human agent, Quiq lets you see exactly where that transfer succeeded or broke down, instead of treating AI performance and human agent performance as two separate reporting systems.

Yes. Quiq connects to your existing reporting stack through BI tool integrations and data export, so your reporting team isn’t limited to what’s inside Quiq’s own dashboards. You can push conversation data, agent performance metrics, and custom event data to your data warehouse, then build on it alongside whatever other business data your team already tracks. Quiq also supports custom events and funnels, so you can track any step in the customer journey, not just conversation-level metrics, and bring in external data to build a genuinely complete view. This is built for teams who want Quiq’s conversation-level intelligence to live inside their broader business reporting, not sit in a separate silo.

Quiq analyzes conversations that transfer between AI and human agents as a single continuous interaction rather than two disconnected records, so you can see exactly where a handoff succeeded and where it didn’t. That includes tracking funnel completion for multi-step processes, like a warranty claim that moves from an AI agent collecting a photo to a human agent handling the escalation, so you know precisely which step is causing conversations to stall. Combined with unified reporting across AI and human agents, this makes it possible to diagnose whether a breakdown is a knowledge gap, an escalation rule that’s too aggressive, or a step in the workflow that customers consistently abandon, instead of guessing from separate systems.