Pylon Metric
Customer Support
CSAT = Positive Ratings / Total Ratings × 100
Customer Satisfaction Score (CSAT) measures the percentage of customers who rate their support experience positively after a Pylon conversation. It is the most widely used indicator of support quality and directly reflects whether agents are meeting customer expectations across all channels.
Full guide: definition, formula, and benchmarksPylonCustomer SupportCustomer Satisfaction Score
Customer Satisfaction Score (CSAT) measures the percentage of customers who rate their support experience positively after a Pylon conversation. It is the most widely used indicator of support quality and directly reflects whether agents are meeting customer expectations across all channels.
How to calculate customer satisfaction score
Why customer satisfaction score matters for Pylon users
CSAT is the most direct measure of whether your support team is delivering value to customers. Declining CSAT is an early warning of process failures, training gaps, or staffing shortfalls that will eventually manifest as churn if left unaddressed.
For Pylon teams, segmenting CSAT by channel, agent, topic, and account reveals where quality varies. A team might achieve excellent CSAT on Slack but poor scores on email, indicating channel-specific process issues rather than a team-wide problem.
Understand and act on customer satisfaction score with KPI Tree
Sync CSAT survey data from Pylon into your warehouse and model the score in KPI Tree. Place it at the top of your support quality tree with agent productivity, resolution time, and first response time as contributing metrics.
Assign RACI ownership to the support manager and set threshold alerts when CSAT drops below target, segmented by channel and team.
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MCPPull metrics from Pylon directly through the Model Context Protocol.
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Related Pylon metrics
Customer Effort Score
Customer SupportMetric Definition
CES = Sum of Effort Ratings / Total Responses
Customer Effort Score (CES) measures how much effort a customer must expend to get their issue resolved through Pylon's support channels. It is captured via post-conversation surveys and strongly predicts customer loyalty - lower effort correlates with higher retention.
Agent Productivity Score
Customer SupportMetric Definition
Agent Productivity Score is a balanced composite metric that evaluates support agent effectiveness across multiple dimensions including conversations handled, resolution time, first-response speed, customer satisfaction, and escalation rate. It avoids over-indexing on volume by equally weighting quality indicators.
First Response Time
Customer SupportMetric Definition
First Response Time = First Agent Reply Timestamp − Conversation Created Timestamp
First Response Time (FRT) measures the elapsed time from when a customer initiates a conversation to when they receive the first human reply from a support agent across any Pylon channel. Speed of initial acknowledgement strongly influences customer perception of the entire support interaction.
Average Resolution Time
Customer SupportMetric Definition
Resolution Time = Conversation Resolved Timestamp − Conversation Created Timestamp
Resolution Time measures the total elapsed time from when a customer opens a conversation across any Pylon channel to when it is marked as resolved. It encompasses first response time, investigation, back-and-forth exchanges, and any internal waiting periods. It is a primary indicator of support efficiency.
Explore customer satisfaction score across integrations
All Pylon metrics
Account Health ScoreAgent Productivity ScoreAgent Specialisation AnalysisChannel Performance AnalysisConversation Handoff AnalysisConversation Sentiment AnalysisConversation Volume TrendsCross-Channel Journey AnalysisCustom Field UtilisationCustomer Contact FrequencyCustomer Effort ScoreEscalation RateFirst Response TimeIssue Category DistributionIssue Recurrence RateKnowledge Gap IdentificationMessage Response Time by PriorityPeak Hours AnalysisRepeat Contact RateAverage Resolution TimeSupport Cost per ContactTag Usage PatternsTeam Workload DistributionEmpower your team to understand and act on Pylon data
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