Chatbot Analytics
Measuring
Measuring
chatbot performance
with clarity
Brelovik tracks what your chatbot actually does — response accuracy, drop-off points, and session resolution rates across every channel. The data is structured so teams can act on it without digging through raw logs.
4.2s Avg. response latency tracked
18+ Performance signals monitored
2016 Year the platform launched
How it works
Structured monitoring at every layer
Each chatbot session generates signal — intent matched, fallback triggered, handoff requested. Brelovik organises these signals into readable layers so nothing gets buried in volume.
Key metrics tracked per session
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Intent recognition rate Percentage of user inputs correctly matched to a defined intent across all active flows.per flow
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Fallback frequency How often the bot reaches a dead end — broken down by entry point and conversation stage.by stage
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Session resolution rate Whether the user's goal was reached without escalation — tracked separately from CSAT.goal-based
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Handoff timing When and why users are transferred to a human agent — with exact trigger context logged.with context
Signal categories available
Response latency Drop-off mapping Channel split Retry patterns Slot fill rate Confidence scores NLP drift alerts
What teams do with this data
Most teams start by fixing the top three fallback triggers — that alone shifts resolution rates noticeably within a few weeks. The platform surfaces which flows need attention, not just that something went wrong.
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Connect your chatbot Brelovik integrates with major platforms via webhook or native connector — no rebuild required.
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Review the baseline report Within 48 hours, a structured report shows where performance sits across all tracked dimensions.
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Work with the group Collaborative sessions with other teams using Brelovik help identify patterns that individual data rarely reveals.