Agent Helper Analytics

Real-time visibility into GenAI adoption, agent behavior, and support outcomes. Built for support leaders, CX heads, and operations teams, Agent Helper Analytics helps organizations move AI from simple enablement to measurable accountability, ensuring GenAI investments deliver tangible operational value. video-thumnail
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The Overview Analytics Dashboard provides a consolidated, executive-ready view of how AI is used, how it performs, and how much value it delivers across the support ecosystem. It combines adoption, efficiency, and collaboration metrics to support data-driven decisions and continuous improvement.

Provides visibility into overall support demand, helping teams benchmark workload and assess how AI scales with case volume.

Highlights resolution throughput over the selected period, enabling leaders to track productivity trends and operational capacity.

Shows the number and percentage of cases closed with Agent Helper involvement, directly indicating GenAI penetration and reliance within real support workflows.

Measures how quickly AI-assisted cases are resolved, helping teams quantify efficiency gains and identify opportunities to reduce resolution cycles.

Tracks cases where Intelligent Swarming was triggered via Slack or email, providing insight into collaboration patterns and complex case handling supported by Agent Helper.

Captures how often AI-generated responses are actively used by agents, serving as a strong signal of trust, usefulness, and day-to-day impact of GenAI assistance.

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Adoption Analytics provides clear visibility into how deeply GenAI is embedded in day-to-day support workflows. These metrics help leaders understand which capabilities are driving value, where adoption is strong, and where targeted enablement can unlock more impact.

Displays the percentage of closed cases where at least one Agent Helper feature was used, helping teams assess real AI penetration across support operations.

Tracks the number of cases where AI-generated responses were used, indicating how effectively agents are leveraging GenAI to accelerate customer communication.

Shows how often AI-generated case summaries are used, highlighting improvements in context building, handoffs, and handling of long-running or transferred cases.

Measures usage of AI-enabled collaboration by tracking cases where swarming was initiated, offering insight into how teams resolve complex issues faster through collective expertise.

Visualizes adoption growth or decline across selected periods, enabling leaders to correlate adoption with enablement efforts, releases, or process changes.

Breaks down usage by agents and teams, helping identify high adopters, coaching opportunities, and best practices worth scaling.

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Feedback Analytics captures direct agent sentiment on AI-assisted outputs, creating a closed feedback loop to continuously improve AI quality, usability, and trust. These insights ensure GenAI evolves based on real-world usage, not assumptions.
Tracks the number of feedback instances submitted by agents, serving as a signal of engagement and willingness to interact with AI outputs.
Provides a high-level quality indicator of AI-generated responses and recommendations, helping teams monitor trust and satisfaction trends.
Analyzes feedback by Agent Helper capability, such as Response Assist or Case Summarization, to pinpoint which features are performing well and which require optimization.
Surfaces common feedback drivers like relevance, accuracy, and usefulness, enabling focused improvements in prompts, models, or content sources.
Captures qualitative comments linked to real cases, giving product and operations teams actionable context behind the metrics.
Monitors how agent sentiment evolves as AI models, configurations, or workflows change, ensuring continuous improvement and sustained trust.
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