3 metrics every support leader should share with product (that actually drive change)
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Why the best support teams today are driving product decisions, not just closing tickets.
For years, support teams have had the closest view of how users experience a product. They know what’s working, what’s not, and where the frustration starts. Meanwhile, product teams own the roadmap that defines the experience—and, ultimately, the value customers get.
But when these two teams speak different languages—or worse, don’t speak at all—vital insights get lost. Feedback loops break down. Opportunities to improve get buried under dashboards and documents.
At DevRev’s Effortless conference, Siddhartha Garikapati, Associate Director of Technical Program Management at Razorpay, highlighted a common disconnect in teams: support teams tend to focus on customer pain, while engineering zeroes in on metrics like latency. Everyone is technically right—but without a shared language, it’s difficult to align on what really needs fixing.
Let’s explore three high-signal metrics that shift the conversation to
- What’s broken?
- How often?
- How urgently does it need attention?
And to understand why these metrics matter, it helps to start with where CSAT and NPS fall short.
Why CSAT & NPS don’t build product strategy
CSAT and NPS are the two popular metrics that support teams have highly focused on to evaluate customer satisfaction, retention, and customer experience for decades. They offer a general pulse of how customers feel and help the support team measure how well they handled a specific interaction.
However, they don’t signal to the product team on what’s broken, how often, or why it needs to be fixed.
A customer saying, “I’m not satisfied,” doesn’t help a product team know why or where to focus. These scores lack specificity, context, and timeliness, which makes them poor signals for product planning.
It’s time to move from measuring how a user felt after support to measuring what made them feel that way in the first place.
3 metrics support team should share with product to build what matters
1. User experience friction
When users repeatedly struggle with core features, UX isn’t working.
Support teams are often the first to detect feature-level usability issues—confusing onboarding steps, inconsistent workflows, or logic that defies user expectations.
This is where user experience friction comes in.
- What it is: The percentage of tickets tied to a specific product area or feature that reflects usability challenges—not necessarily bugs, but confusing flows that make users wander around the tool to figure it out.
- Why it matters: It shows how often your product’s usability is hindered and reveals where UX, logic, or expectations are misaligned, resulting in slow time-to-value and hurt adoption.
You’ll often spot it in clusters when multiple users hit the same wall.
Something like this: “We’ve had 47 tickets on permissions in the last three weeks, mostly from onboarding teams managing $1.2M in ARR—all struggling to figure out setup.”
That kind of pattern is more than a support red flag—it’s a product signal that needs prioritization.
With DevRev’s AI-native support platform, signals aren’t missed. Tickets are auto-tagged by product area, clustered by theme, enriched with session context, and tagged with sentiment. This gives product teams real-time visibility into which features create friction, and how that friction impacts onboarding, expansion, or churn.
2. Issue repeat rate
No one on the product team wants to read the same ticket 50 times. But that’s exactly the problem. What they need is a signal that says:
"This exact issue has been reported 27 times in the last 14 days—take action”.
That’s where the issue repeat rate comes in.
- What it is: The frequency of identical or nearly identical issues being reported through support interactions.
- Why it matters: Repetition = urgency. A one-off ticket might be a fluke. But 19 customers reporting the same bug in a month? That’s a broken experience, and it’s quietly costing you user trust and retention.
Yet most platforms don’t surface this. They bury repetition under raw volume. They don’t connect trends or identify which segments are being hit hardest. And so product teams stay in the dark.
This is where modern support needs to speak the product’s language—with context and clarity.
This could look like: “The ‘CSV Export Failure’ issue was raised 19 times this month—up from 6 last month. And half of those came from customers who are onboarding.”
With DevRev, repetition isn’t something you need to search for or manually tag/group tickets. DevRev’s Smart Clustering uses AI to group similar issues, detect emerging trends, and automatically surface rising patterns—without requiring agents to tag or track manually.
3. Product blockers
Some issues not just annoy users—they stop them from accessing value altogether. These are Product Blockers.
Spotting it early—and surfacing them to the product—is where support makes its biggest impact.
- What it is: Critical issues that prevent customers from completing essential workflows or seeing product value—often phrased as:
“If this doesn’t get fixed, we can’t use your product.”
- Why it matters: Blockers influence adoption, expansion, and renewals. They create internal friction for customers, delay implementation, and can derail entire rollouts.
As Dheeraj Pandey, co-founder and CEO of DevRev, puts it: the customer is not somebody outside the company but is part of the team. “The more siloed we created, the more we thought we were becoming productive, but we really created one of the biggest enemies of team intelligence, which is departments.”
DevRev unifies those silos and turns signals into metrics. It uses urgency scores, ARR tagging, and churn risk prediction to flag blockers in real time. Session analytics and conversation history give full context—so product leaders don’t just see the what, but the why and who.
Aligning support and product teams to drive success
NPS and CSAT tell you how someone felt after support helped. But these three metrics–user experience friction, issue repeat rate, and product blockers–tell you what broke, how often, and how urgent.
Let’s make the contrast crystal clear:
Criteria | User experience friction | Issue repeat rate | Product blocker | CSAT/NPS (Legacy) |
|---|---|---|---|---|
What it captures | Struggles users face with core features or workflows that reflect usability challenges. | Recurrence of identical or similar issues across tickets. | Critical issues that stop customers from completing key workflows. | Emotional response to support, typically post-resolution. |
Why it matters | Highlights friction in UX and misaligned expectations. | Indicates unresolved product gaps that need urgent attention. | Surface high-risk issues tied to adoption, expansion, or retention. | Captures customer happiness levels, but not the underlying product problem. |
Business Impact | Drives roadmap and design decisions by pinpointing friction-heavy areas. | Streamlines backlog and prioritization with issue trend visibility. | Reduces churn and protects ARR by addressing blocking issues early. | Offers insight into the support experience, but it has limited value for long-term product improvements. |
Actionability for the product team | Exposes areas requiring design or flow adjustments. | Aligns product focus with what’s breaking most often. | Escalates must-fix issues with full customer and context data. | Does not provide direct insight into feature or usability issues. |
Value to support teams | Identifies patterns to pre-empt issues and guide users better. | Group similar tickets for faster triage and response. | Prevents fire drills by raising urgent concerns early. | Reflects agent performance, not product experience. |
DevRev’s advantage | AI auto-tags tickets by feature usage patterns and sentiments, and clusters them by themes for real-time visibility into friction points and their impact. | Smart clustering groups similar complaints and detects emerging trends—without requiring agents to tag or track manually. | AI prioritization flags issues based on urgency, ARR impacts, and churn indicators. Session replays give full context of customer issues with fewer questions asked. | Sentiment analysis is helpful, but lacks product-level visibility. |
If you’re a Support leader, start your next product sync with this question:
“Want to know the 3 things making our users hate life this week?”
If you’re a Product leader, connect with your support team counterpart and ask:
“What’s the one issue this week that’s quietly costing us the most trust?”
Turn customer signals into product strategy
Support has always been closer to the customer’s pain, and the product is closest to what gets built to give value to the customer. But the most forward-thinking teams don’t just talk to customers—they talk and listen to each other.
These three metrics are alignment tools that cut through the noise and translate customer pain into product action, with the urgency and clarity both sides need to move forward.
With DevRev’s AI-native insight across support conversations and usage data—the right priorities don’t just rise, they start to accelerate.
Ready to connect the dots between support pain and product action? Let’s show you how DevRev can help. [Book a personalized demo]
