Recurring problems, complaints, and improvements
See granular recurring friction and gaps mapped to product areas.
Klarion surfaces the recurring friction, gaps, and customer impact, so Product teams can protect retention and competitive positioning.
Get a Demo
Klarion turns what customers report in support into structured trends and analysis you can trust.
See granular recurring friction and gaps mapped to product areas.
Prioritize by customer pain, revenue exposure, support cost and clear trends.
Klarion summarizes what’s happening and why, pulling the common thread across many conversations.
Standardized issue patterns reduce confusion and speed decisions on owners and next actions.
Use VoC insights from support conversations to elevate the product experience.
Why it matters: Recurring frustrating issues create customer churn risk.
Klarion delivers A Revenue-at-Risk-ranked view of high-frustration issues by product area.
Why it matters: Unaddressed feedback adds up to erode trust and product satisfaction.
Klarion delivers A volume and frustration-ranked view of recurring problems, complaints, and improvement requests by product area.
Why it matters: Telemetry alone cannot reveal why users abandon features and flows.
Klarion delivers Repeating patterns in customer-reported issues mapped to activation areas.
Why it matters: Unaddressed gaps and friction slow adoption.
Klarion delivers Always-on support data monitoring surfaces issues early so Product can respond faster.
Support conversations contain the customer insights Product needs, but they’re buried in long threads and ticket-level data. Klarion unlocks those insights by extracting the distinct problems, complaints, and improvement requests in each conversation, then standardizing them into consistent patterns over time. The result is product-ready trends you can trust and act on.
Product feedback software helps product managers collect, organize, and prioritize customer needs and product improvement opportunities. Traditional tools often depend on passive wishlists and feedback portals, which capture sporadic input from a limited slice of customers. Klarion redefines this category by extracting product feedback from always-on channels like support tickets and chats. By continuously analyzing active customer conversations, Klarion helps Product teams base strategy and prioritization on current, representative customer feedback, not just the loudest voices in a portal.
Voice of the Customer (VoC) software captures and analyzes feedback to help companies understand customer needs, pain points, and sentiment. It gives Product teams a clearer view of the real customer experience, so product decisions are grounded in what customers are actually saying. While traditional VoC software relies on periodic data collection using structured surveys, Klarion expands VoC by analyzing customer feedback in always-on but “unstructured” channels such as customer support. Support tickets and chats are often one of the richest sources of voice of the customer data because they provide detailed, current, and validated feedback in the customer’s own words
Klarion uses AI to analyze full support conversations, rather than just ticket fields or tags, to identify product issues, complaints, and feature requests. By extracting multiple distinct signals from every transcript, Klarion groups feedback into recurring patterns and quantifies their business impact through metrics like customer frustration, support cost, and revenue risk. This provides Product teams with a faster, more reliable way to perform customer feedback analysis at scale and make decisions based on strategic priorities.
Klarion uncovers recurring product issues by analyzing large volumes of support conversations and grouping similar problems into clear, trackable patterns. This helps Product teams identify which issues occur most frequently, which cause the highest levels of customer frustration, and which gaps have the greatest operational or commercial impact. The result is a more strategic, data-driven view of feature prioritization that moves beyond anecdotal feedback to show the true business cost of every product gap.
Support ticket tags and basic reporting are often inconsistent and limited to one issue per ticket, which distorts product priorities. Unlike manual tagging, Klarion uses AI to analyze full transcripts, allowing it to identify and separate multiple issues contained within a single conversation. By quantifying these patterns using customer frustration, support cost, and revenue risk, Klarion provides a more accurate foundation for product feedback management and ensures teams prioritize based on real business impact rather than just ticket volume.
Klarion helps Product teams prioritize what to fix next by weighing every product issue against three primary business impact metrics: customer frustration, support cost, and revenue risk. Instead of relying on anecdotal feedback or the “loudest voice,” Klarion uses AI to provide a data-driven prioritization framework based on:
This allows Product teams to identify which improvements will have the greatest effect on adoption, retention, and expansion.