From Tickets to Product Truth: How Support Data Powers Better Products

Customer support agents are on the front lines. They directly engage with customers more than any other team. They’re the first to hear what customers like (and dislike) about products and frequently the first to identify issues that create customer friction. This makes CX teams invaluable to their product management counterparts.

Support tickets are teeming with customer signals and often contain the first signs of product problems, but those insights often stay buried in unstructured conversations, fragmented systems, and reactive workflows.

What if your support and product teams could unlock all those insights to turn every ticket into strategic product intelligence? In this world, support doesn’t just resolve tactical problems; it can also reveal where the product strategy needs to evolve. With tight collaboration, the product team also upgrades from just shipping features to closing loops that support has uncovered.

Let’s explore how leading CX and product leaders connect support conversations with real behavioral data to spot friction earlier, prioritize high-impact fixes, and build a continual improvement loop. That new high-speed loop will reduce tickets, improve customer experience, and accelerate product velocity.

Support teams are sitting on untapped product gold

Customer support agents handle hundreds of support inquiries per month, often managing multiple conversations across tickets, calls, emails, and chat at the same time. Each of those conversations provides insight into how customers engage with a product, how it makes them feel, and what they’d like to see change.

Even more powerful than the individual conversations, however, is the aggregate. Support teams are often the first to notice trends related to common pain points, missed expectations, onboarding confusion, and broken workflows. In the past, these trends would come to light in meeting rooms, with one agent sharing an observation and another saying, “I had a customer say that too,” followed by another and another.

Though that still occasionally happens, CX analytics solutions have made systematically spotting issues easier. However, too often, observations still stay within the CX function. Issues get filtered through a support management lens and product teams only hear about the things CX leaders deem most important or pressing to the customer experience.

But product teams want (and need) to hear and understand it all to optimize and build products users love. Support conversations provide immediate, unfiltered feedback and complement what behavioral analytics already suggest. CX support insights provide another important data point for product managers—and it’s invaluable.

From solving tickets to diagnosing product issues

In recent years, executive leaders have (finally) realized that support teams are so much more than ticket takers, shifting the perception of support functions from cost centers to value centers. Delivering exceptional customer experiences is no longer just a competitive differentiator, but a strategic imperative, and support teams are central to making it happen.

Product leaders in particular now recognize the untapped potential of close partnerships with support teams. Today’s support teams not only respond to customer issues but can also interpret patterns that signal product problems. This is a dream come true for product teams because:

• Patterns emerge earlier and can be fixed faster
• Product quality improves through continual feedback loops
• CX improves when support reduces friction at scale

As support takes on a new role (moving from just solving tickets to diagnosing product issues), it creates a new support-product partnership where everyone wins:

• Product teams get insights to build and optimize products faster using the real voice of the customer, not gut instincts
• CX teams gain a deeper product understanding, turning every agent into a more effective problem solver
• Customers benefit from better, more reliable products, proactive communication about potential issues, and empowered support agents

The missing link: connecting support data to product behavior

In most organizations, product and CX leaders meet regularly to discuss observations and opportunities. While that’s great, it’s episodic and incomplete, only providing snapshots of customers’ product behavior. Both teams need real-time access to what’s happening, but support data is too often unstructured, reactive, and disconnected from product workflows.

The good news is there’s now a better way of working. Amplitude helps support and product teams listen to every customer, all the time, on any channel, including how they behave in your product. Above all, Amplitude helps you make sense of customer signals to take action faster.

AI Feedback tells you what customers are really saying in support tickets, reviews, and surveys, surfacing the insights that matter and showing you exactly what to do about it. Agentic AI analyzes all the data and sorts it into actionable product and CX categories.

Unlike other solutions that use off-the-shelf models (GPT, Claude, etc.) that were trained on general internet content, AI Feedback’s LLM-native solution is specifically trained on product feedback patterns. This means it can automatically distill massive volumes of unstructured user feedback data into actionable lists of feature requests, complaints, and other product insights. AI Feedback doesn’t just search for keywords or generate a summary paragraph like a chatbot. Instead, it gives you exactly the right level of detail to build something impactful—enabling your product and CX teams to listen to all your customers and improve outcomes.

With AI Feedback, support teams benefit from:

• AI that automatically tags and clusters similar issues
• Structured insights derived from mountains of individual tickets
• Visibility into the true scale and impact of recurring problems

Similarly, product teams win because:

• Behavioral analytics shows which user segments encounter the most friction
• Funnels reveal exactly where the product breaks
• Impact analysis shows how much an issue affects activation, conversion, retention
  

AI Feedback automatically captures feedback from support tickets, surveys, reviews, social media, and call scripts in one unified dashboard.

Example: Unstructured ticket data becomes actionable product insights

Let’s walk through a practical example of how AI Feedback can turn unstructured data into better products. Imagine it scans customer support conversations and online comments, and finds that the most common request is better shipping notifications. It can even calculate that feedback has come up 500 times.

That’s great. Most CX analytics solutions can do that. But you need more context to take meaningful action. What about the shipping notifications needs to be improved? Do customers want notifications more frequently? Less frequently? Earlier in the process? On different channels? AI Feedback will dive into those 500 comments to understand exactly what customers want.

There’s another huge benefit too: since CX, product, and marketing data are all in one place, you get a deeper understanding of the user experience by analyzing session replays or layering in behavioral data. You can easily create a cohort of users who requested better notifications and dive deeper to find more specifics. You can study their in-product behavior, watch replays of them engaging with notifications, or create a targeted survey to get more information about their perspective on notifications.

With a shared view of product and support data, you can really understand what users say and do.

Cohorts, surveys, and Session Replay close the loop from feedback to action—turning noise into next steps.

How to turn tickets into trends that drive product decisions

Though AI Feedback does the heavy lifting, support and product teams still need a repeatable process to bring these insights to life. Use this operational framework to turn support intelligence into product strategy.

1. Capture + tag automatically: AI turns raw support tickets into structured categories and themes.
2. Cluster recurring issues: Group similar problems to understand volume and underlying product root causes.
3. Quantify through behavioral analytics: Identify which issues happen most often and where in the product they occur.
4. Prioritize by business impact: Which issues affect power users, revenue-driving workflows, or critical funnels?
5. Expose product-ready insights: Turn support patterns into backlog items, UX fixes, and roadmap priorities.
6. Close the loop: Product ships improvements, support sees volume drop, customers experience smoother journeys.

Replit: Support intelligence in action

The team at Replit is on a mission to empower anyone to bring their digital ideas to life, regardless of their technical background, via their full-stack solution for building apps at scale. Amol Jain, Head of Product Engineering, says that engineers and product managers have always been aware of building-related issues and user complaints. However, it was challenging to determine exactly which of these issues was the biggest or most prominent—until AI Feedback.

“In the past, it was so much work to pull data, look through each source, and manually combine them,” he explains. “The fact that AI Feedback was able to collect all of this, really analyze it, gather it, and turn it into a prioritized stack of problems that our users were complaining about made it really easy for us to figure out where to invest, to really prioritize what problems we should go after immediately.”

Fuel the product + support flywheel with support intelligence and Amplitude

No great experience is built in a silo—product, support, or otherwise. Customers demand seamless, connected experiences. The only way to achieve that is clear, unified insights across what they’re doing and saying. When you harness rich support data, and marry it with product and behavioral data, you enable better ways of working.

When support and product teams share the same data, they build experiences customers actually love. Amplitude is the connective tissue that makes this partnership possible.