Burden drivers
Pinpoint what’s driving ticket volume and cost-to-serve, including hotspots and the issues that keep coming back.
Klarion quantifies what’s driving cost, SLA risk, and CSAT decline, so you can prioritize systemic issues and plan capacity.
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Klarion delivers the story behind the metrics, with quantified drivers and priorities you can act on.
Pinpoint what’s driving ticket volume and cost-to-serve, including hotspots and the issues that keep coming back.
Spot SLA exposure, churn signals, and the accounts most likely to escalate before the issue turns operational.
Surface the conversation patterns behind customer frustration so teams can address pain before CSAT starts to slip.
Translate repeated support pain into prioritized fixes your support, product, and operations teams can align around.
Build a Support operation that gets ahead of pain and fire drills.
Why it matters: Capacity decisions need a credible root-cause view.
Klarion delivers: Quantified volume and cost hotspots, plus the issues driving repeat contacts.
Why it matters: Without a shared view, prioritization stalls and teams drift.
Klarion delivers: A shared view of recurring issues and customer impact, grounded in full conversation context.
Why it matters: CSAT can lag before you see it in reporting.
Klarion delivers: Frustration drivers, trend shifts, and rising issue patterns before they hit survey metrics.
Why it matters: Strategic accounts can heat up without warning.
Klarion delivers: Account-level risk signals and clear summaries of what is driving pain.
Why it matters: Post-release surges can snowball fast.
Klarion delivers: Fast detection of what is trending, severity, and impacted customers.
Most support analytics treat each ticket as one data point and every ticket as equally meaningful. That breaks down fast.
Tickets often contain multiple issues, product feedback, and experience feedback. Others are just noise. Klarion fixes the inputs first by separating distinct issues, filtering out non-signal tickets, and standardizing the data over time. The result is trends and findings that Support, Product, and leadership can trust.
Customer support analytics is the systematic process of analyzing support tickets, chats, and service interactions to identify recurring issues, trends, and operational risks. Klarion goes beyond basic metrics, using AI-powered support ticket analytics to reveal the true causes of support costs and customer frustration. This allows support teams to prioritize improvements that reduce the overall support burden while measurable improving service quality and customer satisfaction.
Built-in reporting in platforms like Zendesk or HubSpot is effective for operational ticket counts, but it lacks deeper insights into the root causes of rising support costs and customer pain. It usually stops at the ticket level and misses complex multi-issue conversations. It usually focuses on ticket volume while lacking the ability to quantify actual support effort, customer impact and revenue risk. Klarion adds an advanced layer of customer support analytics by analyzing full transcripts to extract every issue and surface deeper recurring patterns. Klarion’s AI quantifies the support burden, customer frustration and revenue risk. Klarion connects support data with CRM data to help teams monitor account-level support health.
Klarion uses AI-powered analytics to parse full conversations and extract multiple, independent signals from a single ticket. While traditional help desks force a single “tag” onto a conversation, Klarion identifies separate problems, complaints, and help requests within the same transcript and analyzes each independently. This results in more accurate support ticket analytics and a clearer view of what is actually driving support costs, customer pain and revenue risk.
Klarion eliminates noise by automatically filtering out spam, auto-replies, merged tickets, and internal workflow notifications that can distort reporting. In most support environments, a significant portion of tickets does not contain an actual customer issue. By removing this “noise” before the analysis begins, Klarion ensures your customer support analytics are based on real customer interactions, making your trends and prioritization data trustworthy.
Klarion measures customer frustration at the issue level by evaluating indicators of customer effort, impact, sentiment, and escalation risk. Rather than assigning a broad sentiment score to a whole ticket, Klarion assesses how painful each specific issue is for the user. This allows support teams to spot high-friction issues faster and prioritize recurring issues based on the actual degree of customer pain and account risk.
Customer support analytics help Support leaders improve ticket volume reduction, capacity planning, and cross-functional prioritization. By using AI customer support tools like Klarion, leaders gain a clear understanding of which issues create the most operational burden and customer pain. This data-driven approach allows for more effective agent training, faster escalation prevention, and the ability to advocate for product changes that improve both support efficiency and overall product quality.