Real-Time Feedback Applications

They thought they didn't have a culture problem. Our feedback data said otherwise—with timestamps, patterns, and proof. The traditional employee feedback loop is broken: Employee → HR Business Partner → Summarized to Leadership → Often Dismissed Why? Because when feedback is filtered through multiple channels, it loses its impact. By the time leaders hear it, it's just another anecdote. We flipped this model at a medical research organization: • Employees provided feedback directly through our platform • Our system de-identified responses while preserving patterns • Leaders saw aggregated data showing real issues One example revealed a regular "Thursday gathering" where only certain employees were invited. Through our platform: • Employees safely reported feeling excluded (60% more than through traditional channels) • Data showed those not included rated their development opportunities significantly lower • The platform captured specific impacts: "Does this affect your professional development?" "Yes." When leaders saw this data visualization in real-time, there was no room for denial or dismissal. As one HR leader told us: "Before, I'd say 'Some people feel excluded' and get pushback. Now I show the data and leaders immediately ask 'How do we fix this?'" The key innovation isn't just anonymizing feedback—it's transforming individual experiences into undeniable patterns that drive action. When feedback is safe to give and impossible to ignore, real change happens. Let’s get you there.

FeedbackNow began over 15 years ago with the iconic “Green/Yellow/Red” smiley buttons—well-known as the fastest way to gauge customer feelings in the moment and at the point of experience. Lately, we're seeing many clients hit home runs with the often underrated potential of our simple and flexible “123” solution; incredibly powerful for driving real-time operational improvements. We tend to see 3 basic use cases (images below): Empowering Customers: For example, patients can be given the ability to immediately connect with the right department from their bedsides, without pressing the traditional “911” nurse call button or bothering staff with non-clinical requests. This approach has delighted patients at Montefiore Hospital with its simplicity and innovation. Empowering Staff: Staff-to-staff calls can be made with a single click. This simple operation significantly boosts efficiency, saving minutes each time that quickly add up by the end of the day. For example, one VA hospital uses our “123”s to bring the right cleaning staff to emergency room bays with a simple click, saving valuable time and dropping the total wait time of patients down each day. Collecting Precise, Real-Time Location Data: Many organizations rely on surveys to gauge customer opinions. Imagine capturing responses from the exact moment and location they’re asked—giving real-time, actionable insights. My favorite example is an initiative at Q2 Stadium with the Austin Football Club, where a 123 "survey" helped them understand not just how fans got to the game, but also provided a sense of where (which gate) and when. Think about these examples—perhaps you have an innovative idea to use this technology to empower your customers, staff, or data collection? Let us help you create a new, exciting impact! Would love to hear some ideas. #realtime #feedback #CX #FeedbackNow

When you're running voice AI agents at scale, waiting for post-call reports to spot issues is like driving while only looking in the rearview mirror. Real-time monitoring transforms how you manage voice AI performance, letting you catch and fix problems before they impact customer experience. Traditional call center metrics were built for human agents, not AI systems handling thousands of simultaneous conversations. When your AI agent starts struggling with semantic understanding at 2 PM, waiting until tomorrow's report means hundreds of frustrated customers. Real-time monitoring changes the game: → Spot issues instantly, not hours later → Prevent escalation storms before they overwhelm human agents → Optimize confidence thresholds on the fly → Maintain consistent quality regardless of call volume Metrics that actually matter: 1. Latency: Keep response times under 500ms - beyond 1 second, customers hang up. 2. Semantic Accuracy: Track confidence scores and clarification requests in real-time. 3. Live Sentiment: Catch frustration spikes before they become escalations. Your voice AI needs a nervous system, not just a brain. Real-time monitoring is that nervous system - giving you instant feedback to maintain the quality your customers expect. Precisely what we’re solving for at Leaping AI (YC W25).

Can a virtual program with real time feedback using natural language processing help teachers create better math lessons? 💻 Yasemin CopurGencturk and Jingxian Li (both of the USC Rossier School of Education) and Sebnem Atabas set out to answer this question with their paper (link in the comments) published in May 2024. 💡 The findings? Researchers created an online program that gives teachers real time feedback using intelligent tutoring systems. In the study, teachers who used the program developed richer math lessons and connected ideas better, helping students understand math concepts more clearly. This shows that smart, interactive training can make a measurable difference in how teachers teach with impacts on student learning. 📄 Full abstract: Scalable and accessible professional development programs have the potential to address the opportunity gap many teachers experience. Yet many asynchronous online programs lack interaction with and timely feedback to teachers. We addressed this problem by developing a virtual, interactive program that uses intelligent tutoring systems to provide just‐in‐time feedback to teachers. We conducted a randomized controlled trial with teachers across the United States in which teachers were assigned to either this program or no additional training. We found that teachers who completed our program (N = 29) used mathematically richer tasks and created a more coherent, connected learning environment for students to build conceptual understandings than did teachers who were in the business‐as‐usual condition (N = 23). ✳ Like the last research paper, this studied natural language processing (and not generative AI). #genaiedimpact

User Feedback Loops: the missing piece in AI success? AI is only as good as the data it learns from -- but what happens after deployment? Many businesses focus on building AI products but miss a critical step: ensuring their outputs continue to improve with real-world use. Without a structured feedback loop, AI risks stagnating, delivering outdated insights, or losing relevance quickly. Instead of treating AI as a one-and-done solution, companies need workflows that continuously refine and adapt based on actual usage. That means capturing how users interact with AI outputs, where it succeeds, and where it fails. At Human Managed, we’ve embedded real-time feedback loops into our products, allowing customers to rate and review AI-generated intelligence. Users can flag insights as: 🔘Irrelevant 🔘Inaccurate 🔘Not Useful 🔘Others Every input is fed back into our system to fine-tune recommendations, improve accuracy, and enhance relevance over time. This is more than a quality check -- it’s a competitive advantage. - for CEOs & Product Leaders: AI-powered services that evolve with user behavior create stickier, high-retention experiences. - for Data Leaders: Dynamic feedback loops ensure AI systems stay aligned with shifting business realities. - for Cybersecurity & Compliance Teams: User validation enhances AI-driven threat detection, reducing false positives and improving response accuracy. An AI model that never learns from its users is already outdated. The best AI isn’t just trained -- it continuously evolves.