The personal story behind building Feedric—how scattered feedback across tools led to a solution that helps teams organize customer feedback from multiple sources.
It was 2 AM, and I was scrolling through Slack channels, searching for a customer complaint I knew existed somewhere. I'd seen it earlier—or was it in an email? Maybe it was in a support ticket? The frustration was real: I had valuable feedback scattered across five different tools, and I couldn't find the one piece of information I needed to make a critical product decision.
That moment was my wake-up call. I wasn't alone in this struggle. Every team I knew was drowning in feedback—drowning in the very information that should be helping them build better products. That night, Feedric was born.
As I talked to more teams, I discovered five universal pain points that were costing companies hours every week and, more importantly, costing them customers.
Picture this: A customer mentions a bug in Slack. The same issue gets reported via email. Someone else posts about it in a support ticket. Your team discusses it in a meeting, and notes end up in Google Docs. By the time you're ready to fix it, you have no idea where all the information lives.
Teams waste 5-10 hours per week just searching for feedback they know exists. The information is there—it's just everywhere at once, with no single source of truth.
Sarah, a product manager I spoke with, described it perfectly: "We get hundreds of messages a day. I know there's gold in there—critical feedback that could change our roadmap. But I can't process it all. I end up making decisions based on the last three things I read, not the most important things."
When feedback volume exceeds your capacity to process it, you don't just miss opportunities—you make decisions with incomplete information. The signal gets lost in the noise.
Every Monday, teams spend hours manually sorting feedback into spreadsheets: bugs here, feature requests there, complaints in another column. It's tedious, it's error-prone, and it's the same work, week after week.
What makes it worse? Different team members categorize things differently. What one person calls a "bug" another calls an "improvement." The inconsistency makes it impossible to trust your own data.
You remember a customer asking about a feature, but you can't find it. You search for "dashboard customization" but nothing comes up. Later, you discover three different customers asked about "personalizing the dashboard" and "making the UI customizable"—the same request, different words.
Traditional keyword search fails because it doesn't understand meaning. You miss patterns, you miss connections, and you make decisions without the full picture.
This one hit me hardest. A customer success manager told me about a client who churned. "Looking back, the warning signs were all there," she said. "Negative feedback in Slack, complaints in support tickets, declining engagement. But by the time I saw the pattern, it was too late."
Churn signals exist in feedback—frustration, repeated complaints, declining sentiment. But when feedback is scattered and unanalyzed, those signals go unnoticed until it's too late.
The vision was simple: bring all feedback into one place, understand it automatically, and make it searchable by meaning, not just keywords. The execution? That required solving some interesting challenges.
I needed to connect to multiple platforms in real-time—Slack, email, support tickets. I needed AI that could categorize feedback accurately (we're talking 99.5% accuracy here). And I needed search that understood meaning, not just exact word matches.
The breakthrough came with semantic search—using AI to understand the meaning behind words. Now, when someone searches for "dashboard customization," they find feedback about "personalizing the UI" and "making it customizable." The system understands these are the same concept, even though the words are different.
Feedric doesn't just store feedback—it understands it. Using AI-powered categorization and semantic search, it finds connections you didn't know existed. It surfaces patterns across different sources, different time periods, and different ways of expressing the same idea.
This isn't just about organizing data. It's about giving teams the full context they need to make better decisions, faster.
Building Feedric taught me that the best solutions come from understanding real problems. Every technical decision I made was driven by a pain point I'd witnessed or experienced myself.
Real-time integration? Because teams need feedback the moment it arrives, not hours later. AI categorization? Because manual sorting doesn't scale. Semantic search? Because keyword matching misses the connections that matter.
But the most important lesson was this: when feedback is organized, searchable, and understandable, teams don't just work more efficiently—they make better decisions. They catch churn signals early. They prioritize based on data, not guesswork. They build products customers actually want.
Feedric is still evolving. We're adding new integrations, improving our AI, and learning from every team that uses it. But the core mission remains the same: help teams turn scattered feedback into actionable insights.
If you've ever spent hours searching for feedback you knew existed, or made a decision without the full context, or watched a customer churn when the warning signs were there all along—you're not alone. And you don't have to keep doing it this way.
If you're interested in seeing how Feedric can help your team organize customer feedback from multiple sources, check out our documentation or start a free trial. Let's turn your scattered feedback into your competitive advantage.
Start your free 14-day trial and see how Feedric can help you organize and prioritize feedback automatically.
Get Started Free