Implementing User Feedback in Support Tool Design

I used to think user research was easy. But then I switched to B2B. And oh boy... reality hit hard Back when I was working on a B2C product, I could run 10 user interviews in a day. Users would happily spend 45 minutes answering questions and testing new designs. I thought this was just regular product design. Turns out, I was riding a perfect wave of continuous discovery without even realizing it. Then I switched to B2B. And I admit it really felt scary at first. Users were just too busy to pick up my phone calls. It took 3 weeks to schedule 5 calls. Some users left a bad CSAT score with barely any comment. Damn. How can we build anything serious without ever talking to users? At that time, it really felt like an impossible task. And any way I tried to put it, there were just no efficient process to get those users on the phone. But then it hit me. What if the best discovery touch points weren’t designers or PMs at all? What if they were already happening… in sales calls, support chats, internal Slack threads? And we had this feedback scattered across tools, threads, and people. But no one was making sense of it. So we built a Feedback Management System. We plugged every feedback into a single source of truth directly in Notion: - Intercom conversations and Modjo calls with customers - Internal tickets from sales and support to discuss user pain points or feature requests - User feedback forms submitted on the platform All filtered and organized per team through Notion automations. Each designer spends 2 hours per week turning raw feedback into structured insights. Then each team reviews it together weekly, and it feeds product decisions and the roadmap. It’s simple. It’s scalable. And it changed everything. Product designers no longer design based on shaky assumptions or partial data. They're now the source of customer truth and alignment. In B2B, discovery doesn’t happen in a lab. It happens in the wild. You just need to know where to listen. #productdesign #uxdesign #userresearch

How listening to agents transformed our AI for customer support! When we set out to build AI tools for customer support, we had a decent idea of what to create. Or so we thought. It wasn’t until we sat down with agents and asked how they were actually using AI that we had our “aha” moment. One conversation, in particular, stood out. We were speaking with Paula, an agent, and asked if she was leveraging any AI tools in her work. She showed us her process: Paula would copy entire customer chats, paste them into the Gemini window, and type instructions like, "We don’t offer returns- please make this message empathetic.” The AI would then craft a beautifully worded response that Paula would use to handle the situation. That’s when it hit us: while our AI was functional, a small tweak could make it incredibly impactful. We immediately got to work and introduced a feature allowing agents to refine responses directly within our product. Whether they needed a message to be more empathetic, friendly, or professional, the AI could adapt on the fly - no more copy-pasting or switching between tools. Paula’s workflow became significantly faster and smoother. She could focus on solving customer issues rather than navigating between platforms. This experience reinforced something crucial: building great products starts with listening to the people who use them. Have you had a moment where user feedback completely reshaped your product? #ai #customersupport #productdevelopment #virtualagents

𝗦𝘂𝗽𝗽𝗼𝗿𝘁 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 🧩 is the missing puzzle piece product needs. Here how to snap it into place: Support teams → You're sitting on a goldmine of insights. Product leaders → You're probably not hearing them. 1. 𝗧𝗵𝗲 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗪𝗮𝘆: 𝗦𝗺𝗮𝗿𝘁 𝗧𝗮𝗴𝗴𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝘠𝘰𝘶 𝘥𝘰𝘯’𝘵 𝘯𝘦𝘦𝘥 𝘈𝘐 𝘵𝘰 𝘤𝘳𝘦𝘢𝘵𝘦 𝘢 𝘴𝘵𝘳𝘰𝘯𝘨 𝘧𝘦𝘦𝘥𝘣𝘢𝘤𝘬 𝘭𝘰𝘰𝘱. 𝘚𝘵𝘢𝘳𝘵 𝘩𝘦𝘳𝘦:  • Start w/ 10 tags tied to actual customer problems (ask your best agent or export your data and ask AI)  • Make them specific (e.g., “Dashboard_Loading_Speed” > “Performance”)  • Train support to tag consistently (this is where most teams fail)  • Track weekly trends and build monthly impact reports  • Identify which issues cause the most customer pain 🛠 We started with just 10 core tags—and refined over time and nowuse 100s. Each week, ask: ↳ What came up most often? ↳ What took the longest to resolve? ↳ What ONE fix would move the needle most? It works—but it’s manual, and easy to miss emerging trends. 2. 𝗧𝗵𝗲 𝗠𝗼𝗱𝗲𝗿𝗻 𝗪𝗮𝘆: 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗩𝗼𝗶𝗰𝗲 𝗼𝗳 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝘈𝘐 𝘴𝘶𝘱𝘱𝘰𝘳𝘵 𝘵𝘰𝘰𝘭𝘴 𝘩𝘢𝘷𝘦 𝘤𝘩𝘢𝘯𝘨𝘦𝘥 𝘵𝘩𝘦 𝘨𝘢𝘮𝘦: • Analyze 100% of support conversations • Tickets are auto tagged by AI which can trigger workflows • Use NLP to detect themes without tags • Surface hidden friction points, grouped by sentiment   My Support Ops team shares insights like: ↳ New friction points by user segment ↳ Confusing UX patterns ↳ Estimated support cost per issue ↳ Predicted impact of potential fixes 🔍 We recently spotted a major adoption blocker invisible in product metrics—but obvious in support conversations. The result? Better prioritization, faster fixes, happier customers. Whether you're leading support or building product, this is the shift: Customer feedback shouldn’t be anecdotal—it should be operational. Support has the data. Product needs the context. The puzzle only clicks when both sides connect. P.S. Which method are you using today? ———————————— 📩 𝘞𝘢𝘯𝘵 𝘧𝘳𝘰𝘯𝘵𝘭𝘪𝘯𝘦 𝘢𝘥𝘷𝘪𝘤𝘦 𝘢𝘯𝘥 𝘧𝘳𝘦𝘴𝘩 𝘱𝘦𝘳𝘴𝘱𝘦𝘤𝘵𝘪𝘷𝘦 𝘦𝘷𝘦𝘳𝘺 𝘰𝘵𝘩𝘦𝘳 𝘸𝘦𝘦𝘬? 𝘛𝘰𝘱-𝘛𝘪𝘦𝘳 𝘚𝘶𝘱𝘱𝘰𝘳𝘵 𝘥𝘦𝘭𝘪𝘷𝘦𝘳𝘴 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘪𝘦𝘴 𝘵𝘰 𝘦𝘭𝘦𝘷𝘢𝘵𝘦 𝘴𝘶𝘱𝘱𝘰𝘳𝘵 𝘭𝘦𝘢𝘥𝘦𝘳𝘴. [𝘭𝘪𝘯𝘬 𝘪𝘯 𝘱𝘳𝘰𝘧𝘪𝘭𝘦]

Feedback can sting. In July, some customers told me our platform was too complex. When this happens, you have 2 choices: ↳ Blame the user for not “getting it.” ↳ Or listen, and make it easier. I chose to listen. Here are 5 actionable steps I implemented in the following 2 weeks: 1/ Gathering every comment, complaint, and suggestion. 2/ Looking for a pattern: too many options, not enough direction. 3/ Creating pre-built workflows: simple, guided paths to value. 4/ Rolling them out fast, not months later. 5/ Measuring the before and after: time to value, ease of use, and customer satisfaction. It’s the first week of August, and the results speak for themselves: → Customers got results faster. → Fewer people felt lost. → Support tickets dropped. → More users reached their goals. If you want to build something people love, listen hard. Act fast. Make it easier, not harder. PS: marketbetter (mb)ᵃⁱ just deployed some new workflows - shoot me a DM to test them for free - Sunder S.

Your customers are telling you exactly how to create a better product—are you listening? I've worked with a lot of companies and used a lot of feedback systems. The ones that work the best require categorizing and prioritizing them so the company is tackling the most important issues first. Slack does this well. To ensure that user feedback directly influenced product development, Slack refined its feedback collection and integration process. They implemented tools and processes to categorize feedback effectively and route it to the appropriate teams quickly. This systematization of feedback collection and analysis enabled Slack to prioritize product updates and feature requests more efficiently, leading to faster iterations and improvements that closely aligned with user needs. How can you tag and prioritize your feedback so you are focused on the most important issues?

Following user feedback is a Product Management virtue. Is there an actual way to implement it, between all the noise, bugs, and stakeholder requests? Well… Most teams claim they are customer-driven. Yet the moment you open Zendesk, App Store reviews, survey results, and Slack threads, you instantly remember why everyone quietly avoids this work. Feedback is everywhere, contradictory, emotional, duplicated, and nearly impossible to turn into decisions.  It is chaos disguised as “insights.” This is why the new Amplitude AI Feedback release caught my attention and made it all the easier to decide to partner with them on this update. It successfully connects what users say with what they actually do, in one workflow. No extra tools.  No extra tabs. You see their words, frustrations, and praise. You see their behavior. And AI transforms it into ranked themes, rising trends, top requests, and complaints. Noise turns into clarity. Opinions turn into patterns. Patterns turn into action. And because it is native inside Amplitude, it kills the biggest problem in feedback work: Fragmentation. Everything flows into analytics, session replay, and cohorts, creating a full loop from insight to fix. You can trace why an issue matters, how many users care, how it impacts behavior, and which actions you should take. Finally, a single source of truth for PMs, UX, CX, and marketing. I’m also genuinely impressed with the supported sources of feedback: App Store, Google Play, Zendesk, Intercom, Freshdesk, Salesforce Service, Gong, Trustpilot, G2, Reddit, Discord, and X. Slack arrives in Q1, and there will be more! If you ever felt overwhelmed by feedback, this is one of the first attempts I have seen that genuinely solves the operational pain, not just the reporting part. It launches… Today! Take a look: https://lnkd.in/dAJKeTez What was the most successful update you know that came from the product’s users? Let me know in the comments. #productmanagement #productmanager #userfeedback

We don’t guess what users want we ask… That’s how we build digital products users rely on. Here’s how we make feedback the superpower behind great UX 👇  Step 1: Listen Deeply We run: ‣ 1:1 user interviews ‣ In-app surveys & session recordings ‣ Live usability testing  Step 2: Turn Chaos into Clarity We map raw feedback into themes: ‣ Usability issues (e.g. confusing navigation) ‣ Feature gaps (e.g. missing integrations) ‣ Friction points (e.g. slow checkout) Step 3: Design, Test, Validate We co-create with your team: ‣ Interactive prototypes (Figma) ‣ Real user validation before dev ‣ Accessibility & performance checks  Step 4: Ship Fast, Measure Faster Every improvement is: ✔️ A/B tested ✔️ Backed by analytics ✔️ Tied to measurable ROI Who This Helps ‣ SaaS & Tech → Reduce churn, improve onboarding ‣ Fintech → Simplify UX, boost adoption ‣ Healthcare → Design for clarity & trust ‣ Enterprise tools → Optimize internal workflows What You Get ✅ UX audit + feedback dashboard ✅ High-fidelity mockups & tested flows ✅ Real user insights + recordings ✅ Optional: Monthly UX performance reports 💡 User feedback is the fastest way to build what people love. Let’s make it part of your product growth strategy.