Customer Feedback Utilization

Surveys can serve an important purpose. We should use them to fill holes in our understanding of the customer experience or build better models with the customer data we have. As surveys tell you what customers explicitly choose to share, you should not be using them to measure the experience. Surveys are also inherently reactive, surface level, and increasingly ignored by customers who are overwhelmed by feedback requests. This is fact. There’s a different way. Some CX leaders understand that the most critical insights come from sources customers don’t even realize they’re providing from the “exhaust” of every day life with your brand. Real-time digital behavior, social listening, conversational analytics, and predictive modeling deliver insights that surveys alone never will. Voice and sentiment analytics, for example, go beyond simply reading customer comments. They reveal how customers genuinely feel by analyzing tone, frustration, or intent embedded within interactions. Behavioral analytics, meanwhile, uncover friction points by tracking real customer actions across websites or apps, highlighting issues users might never explicitly complain about. Predictive analytics are also becoming essential for modern CX strategies. They anticipate customer needs, allowing businesses to proactively address potential churn, rather than merely reacting after the fact. The capability can also help you maximize revenue in the experiences you are delivering (a use case not discussed often enough). The most forward-looking CX teams today are blending traditional feedback with these deeper, proactive techniques, creating a comprehensive view of their customers. If you’re just beginning to move beyond a survey-only approach, prioritizing these more advanced methods will help ensure your insights are not only deeper but actionable in real time. Surveys aren’t dead (much to my chagrin), but relying solely on them means leaving crucial insights behind. While many enterprises have moved beyond surveys, the majority are still overly reliant on them. And when you get to mid-market or small businesses? The survey slapping gets exponentially worse. Now is the time to start looking beyond the questionnaire and your Likert scales. The email survey is slowly becoming digital dust. And the capabilities to get you there are readily available. How are you evolving your customer listening strategy beyond traditional surveys? #customerexperience #cxstrategy #customerinsights #surveys

A lot of people talk about AI tools. Here’s a simple, no-frills way I use AI as a PM to save 10 hours every week. The best part? It took under 3 hours to set up. 1️⃣ Meeting Notes → Obvious, but Underused Most teams already use an AI note-taker. You've seen how it works. What matters: The quality of output reflects the clarity of your contribution. If you speak vaguely in meetings, AI captures that. Since using Fireflies or Fathom, I've become intentional about articulating decisions and actions out loud. AI doesn't just write what you say. It reveals how you think in real time. 2️⃣ Customer Feedback → Surface What Teams Aren't Discussing The biggest value of feedback analysis isn't speed, it's exposure to signals outside existing assumptions. A fintech company applied AI clustering (Thematic, ChatGPT) over 4,000 support tickets. The tool surfaced emerging behaviour: customers manually exporting data to track regulatory deadlines. This wasn't raised internally. Six weeks later, they launched automated compliance reminders. That feature now drives ~18% of new conversions. Speed didn't create the insight, unfiltered pattern detection did. 3️⃣ Documentation → Write to Clarify, Not Expand A good PRD refines thought, not volume. My process: 10-min brain dump → AI draft → manual refinement on strategy and edge cases. Tools: ChatGPT, Claude Time on formatting: Almost zero Time on strategic clarity: Significantly higher "Advanced Filters" PRD took 45 minutes. It wasn't shorter, it was sharper. 4️⃣ Competitive Intelligence → Track Less, Interpret More Monitoring six competitors weekly took time without changing decisions. Now, Crayon or Claude surfaces market movements automatically. My role is interpreting why the opponent moved and where the next move lies. When a competitor shifted to freemium, we reframed our Q2 pricing narrative within 24 hours, highlighting configurability they couldn't match. The insight wasn't from the alert, but from owning the context. 5️⃣ Reporting → Let AI Write, You Explain Traditional reporting chews through half a Friday: pulling metrics, formatting, summarizing. Now: Export data → feed into ChatGPT or Notion AI → AI assembles structure → I add operational context. Reports go out Friday evening. Mondays start with action, not explanation. Important: AI captures what's visible. You still own interpretation. If this gave you ideas, a like or repost helps it reach more PMs who need it. Best, Akhil

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.

Our designer Rishikesh spends an hour every day watching users get stuck. Every morning at 10 AM, he watches session recordings on 4x speed, looking for the moment users pause too long, click the same button twice, or try the same action again. Here’s a tiny example from last week. Users wanted to download their finished deck. But instead of clicking the download button, many of them were typing "download" into the agent. That is a product failure. The user should not have to ask the agent to do something the interface already supports. So Rishi made a small change: when users typed keywords like "download," we automatically surfaced the download button right where they needed it. The result: agent and support requests about downloading dropped to zero. Last month, we caught 14 patterns like this. Most were invisible in our analytics dashboard. This is why we watch users get stuck. Not because we enjoy watching people struggle. Because this is where the roadmap often hides. A support ticket tells you what a user could articulate. A behavior trace tells you what they actually experienced. The best product insights are often not in what customers say they want. They are in what customers keep trying to do despite your product fighting them. Founders/product teams: what is one thing your users keep trying to do that your product keeps fighting them on?

Don't reject unconventional use of your products. Embrace unanticipated ways that your customers use your products. 🚀 As product managers, we design, develop, and forecast how our products would be used by customers. But what happens when our customers surprise us by employing our products in entirely unexpected ways? Some examples 💡 Collaboration tools like Slack or Microsoft Teams were designed to facilitate team communication and project management. However, users have expanded their use cases by creating virtual communities, hosting webinars, or even organizing online events and conferences. 💡 Ride-sharing services like Uber and Lyft were originally created as an alternative to traditional taxis. However, users have found additional uses, such as using these services for deliveries, running errands, or even as a means of transportation for their pets. 💡 Crowdfunding platforms like Kickstarter or Indiegogo were designed to help individuals raise funds for creative projects. Users have extended their use cases to include launching new product lines, funding charitable initiatives, or even validating market demand for new business ideas. Instead of resisting unexpected customer usage, product managers should eagerly embrace the unanticipated, reaping the rewards of uncharted territory. 1️⃣ Listen and Learn: Actively seek feedback from your customers and diligently monitor their usage patterns. Their unanticipated usage reveals new needs and pain points, allowing you to unlock innovation and tailor your product more effectively. 2️⃣ Adapt: Embrace the mantra of flexibility and adaptability. By tweaking your product roadmap to incorporate unexpected use cases, you can stay ahead of the curve and respond to emerging customer demands with agility. 3️⃣ Redefine User Research: Traditional user research focuses on expected use cases, but true insights lie in understanding the context and motivations behind unexpected usage. Dive deeper into your customers' experiences to unveil hidden opportunities and build stronger, more customer-centric products. #productmanagement #productleadership #productinnovation #productdesign

That’s the thing about feedback—you can’t just ask for it once and call it a day. I learned this the hard way. Early on, I’d send out surveys after product launches, thinking I was doing enough. But here’s what happened: responses trickled in, and the insights felt either outdated or too general by the time we acted on them. It hit me: feedback isn’t a one-time event—it’s an ongoing process, and that’s where feedback loops come into play. A feedback loop is a system where you consistently collect, analyze, and act on customer insights. It’s not just about gathering input but creating an ongoing dialogue that shapes your product, service, or messaging architecture in real-time. When done right, feedback loops build emotional resonance with your audience. They show customers you’re not just listening—you’re evolving based on what they need. How can you build effective feedback loops? → Embed feedback opportunities into the customer journey: Don’t wait until the end of a cycle to ask for input. Include feedback points within key moments—like after onboarding, post-purchase, or following customer support interactions. These micro-moments keep the loop alive and relevant. → Leverage multiple channels for input: People share feedback differently. Use a mix of surveys, live chat, community polls, and social media listening to capture diverse perspectives. This enriches your feedback loop with varied insights. → Automate small, actionable nudges: Implement automated follow-ups asking users to rate their experience or suggest improvements. This not only gathers real-time data but also fosters a culture of continuous improvement. But here’s the challenge—feedback loops can easily become overwhelming. When you’re swimming in data, it’s tough to decide what to act on, and there’s always the risk of analysis paralysis. Here’s how you manage it: → Define the building blocks of useful feedback: Prioritize feedback that aligns with your brand’s goals or messaging architecture. Not every suggestion needs action—focus on trends that impact customer experience or growth. → Close the loop publicly: When customers see their input being acted upon, they feel heard. Announce product improvements or service changes driven by customer feedback. It builds trust and strengthens emotional resonance. → Involve your team in the loop: Feedback isn’t just for customer support or marketing—it’s a company-wide asset. Use feedback loops to align cross-functional teams, ensuring insights flow seamlessly between product, marketing, and operations. When feedback becomes a living system, it shifts from being a reactive task to a proactive strategy. It’s not just about gathering opinions—it’s about creating a continuous conversation that shapes your brand in real-time. And as we’ve learned, that’s where real value lies—building something dynamic, adaptive, and truly connected to your audience. #storytelling #marketing #customermarketing

Most teams guess what to build. We talk to 100s of prospects a month and let them tell us exactly what’s broken. In the early days of Salesforge, we knew one thing: The company that talks to the most customers the fastest… wins. That’s why we book 10–20 meetings a day not just to sell, but to learn faster than anyone else in our category. Every single day, we hear what prospects hate, where their current stack fails, what gets them excited, and what they wish existed. That learning compiles. It compounds. And over time, it becomes your strategic edge. Here are 4 lessons we’ve learned by doing this at volume and how it’s shaped how we build: 1. Feedback isn’t optional Most teams try to prioritize based on opinions, roadmaps, or investor pressure. We don’t. We let volume of feedback decide what gets built and what doesn’t. When you’re on 100+ calls a week, patterns become undeniable. If 6 out of 10 people mention the same workflow friction — we tag it, push it to product, and ship fast. Sometimes within a week. Without this level of signal clarity, you risk overbuilding, building in the wrong direction, or even worse — building something nobody wants. Velocity of feedback → velocity of learning → velocity of execution. 2. The best ideas don’t live on a whiteboard We’ve never treated the roadmap as a fixed blueprint. It’s a living document that adapts with every conversation. Some of our biggest wins started out as throwaway questions from prospects: “Can you guys do this?” “What if your agent could also handle that?” When you hear something like that three, four, five times in a single week, it’s no longer a fluke. It’s a market pull. We’ve built entire products like Warmforge and Leadsforge based on patterns that showed up first in conversations. Too many teams fall in love with their own ideas. We fall in love with patterns. 3. Repetition forces clarity or it exposes fluff If you’ve ever delivered the same pitch 50+ times in a week, you know one thing: you can’t fake it. If your messaging isn’t sharp, people will tune out. That’s the beauty of repetition. It either breaks your narrative or forces you to tighten it. Every meeting becomes a stress test for your story. 4. Geography matters more than you think One of the most underappreciated lessons we’ve learned from talking to prospects globally is just how different buyer behavior is by region. → Southeast Asia and LATAM? WhatsApp. → US? Email + cold call + LinkedIn → Europe? Email + cold call + LinkedIn + Whatsapp Without the conversations, we’d be shipping the wrong thing into the wrong market. TAKEAWAY Most teams optimize for pipeline. We optimize for learning velocity. That’s how you ship products people want. That’s how you write copy that converts. That’s how you build an agent that actually works in the wild. And the only way to do it? Listen harder. Track everything. Move fast. It’s messy. It’s unscalable. And it’s the reason we’re winning.

When the Head of Product drives strategy top-down, PMs get frustrated. But when PMs drive bottom-up planning...execs get nervous. And when they don’t talk? Roadmaps fall apart. The best product planning lives in the middle. You need top down planning and bottom-up discovery Too often, orgs pick just one side: 🧠 Top-down: Execs set bold bets. PMs execute — even when the data says “this won’t land.” 👟 Bottom-up: PMs chase user needs. Strategy gets lost in the backlog. Here’s what works: strategy as a loop, not a broadcast. 1️⃣ Set Strategic Guardrails Top-down strategy should provide the North Star. Not a list of features. But a set of outcomes: → What problems are we trying to solve at the business level? → What does success look like 12–24 months out? Think: revenue targets, market positioning, platform investments. PMs need these boundaries to prioritize with purpose. 2️⃣ Run Bottom-Up Discovery This is how we understand customer value. → Who is the core customer? → Where's the true pain point? → What patterns are emerging across segments? Not just voice-of-customer — real behavior, real usage. PMs should synthesize signal, not just collect noise. 3️⃣ Drive the Planning Loop Now comes the hard part: translation. → Which bottom-up signals align with strategic goals? → Where do they challenge the current direction? This is where planning becomes strategic. You’re not just slotting features into a timeline — you’re shaping the roadmap based on live feedback. Push for course-correction before commitments solidify. 4️⃣ Package for Executive Buy-In Insights only drive action when they’re communicated in the right language. → Use exec framing: risk, revenue, roadmap. → Use BLUF and the 5-slide rule. → Show tradeoffs, not just problems. This is where influence happens — not just up, but across product, design, eng, marketing. Final thought: The best strategy lives at the intersection of business value and customer value. Not just vision. Not just feedback. Real planning that connects the two. -- 👋 I’m Ron Yang, a product leader and advisor. Follow me for insights on product leadership & strategy.

Most restaurant operators think about competitors the wrong way. It’s not just about beating the guy down the street. It’s about knowing where you can improve vs where you’re already winning. When I talk with operators about competitor insights, I like to use this simple framework: The Competitive Strengths & Opportunities Matrix: 💪 Strengths to Promote – Guests love you here and you outperform the market—shout it from the rooftops. 🔧 Opportunities to Differentiate – You’re ahead of competitors, but guests still see room for growth—keep improving until they love this category. ⚖️ Competitive Gap – You’re behind competitors even though guests rate you positively—decide whether to close the gap or let them own it. 🛑 Definite Risk – Guests rate you low and you trail the market—address these urgently to protect guest loyalty and brand reputation. How to Use It in Practice: 1) Pull your data – Guest feedback + online review sentiment + market comparisons. (Our newly released Competitive Pulse feature makes this so easy!) 2) Plot each category – See where you’re strong and where you’re vulnerable. 3) Prioritize actions – Promote strengths, fix risks, improve differentiation, and decide on competitive gaps. 4) Repeat quarterly – Track progress over time. With Competitive Pulse—part of Ovation’s Summer Release—you can compare each of your locations with up to 5 competitors and gain a market perspective instantly, without manually reading every competitor review. How do you approach competition?

I built a Clay workflow to monitor brand mentions across social media and turn them into GTM signals my team can act on. Most teams either ignore social chatter, drown in it or react when their investor sends them something they saw. None of these works. They lack a strategy and a system to enable social listening. My Clay workbook listens across Reddit, LinkedIn, and Twitter/X, analyzes sentiment, summarizes the context, and drops a clean signal straight into Slack. Here’s how the workflow works: – Pull brand mentions from Reddit, LinkedIn company mentions, and Twitter/X keywords – Visit the source URL to extract the actual post text – Analyze sentiment and assign a score so you know if it is positive, neutral, or risky – Generate a short summary instead of dumping raw text – Send everything into a dedicated Slack channel in near real time What I love most about this is how many use cases this unlocked. If sentiment is positive, you get instant feedback on what messaging resonates. If sentiment is negative, you catch brand risk early before it spreads. If buyers are talking about a problem you solve, you spot pipeline signals hiding in public conversations. And because this lives in Clay, you control everything: Keywords, sources, frequency, models and event costs. This replaces expensive social listening tools and gives GTM teams something better... a living feedback loop tied to action. If you want the full walkthrough and Clay template, it's in this week's Stack & Scale episode. Or comment "Clay workflow" AND connect with me (I've run out of InMail already), and I'll send the resources directly. Happy (social) listening!