Gathering Real-Time Customer Feedback During Development

Too many product teams believe meaningful user research has to involve long interviews, Zoom calls, and endless scheduling and note-taking. But honestly? You can get most of what you need without all that hassle. 🙅♂️ I’ve conducted hundreds of live user research conversations in early-stage startups to inform product decisions, and over the years my thinking has evolved on the role of synchronous time. While there’s a place for real-time convos, I’ve found async tools like Loom often uncover sharper insights—faster—when used intentionally. 🚀 Let’s break down the ROI of shifting to async. If you want to interview 5 people for 30 minutes each, that’s 150 minutes of calls—but because two people are on the call (you and the participant), you’re really spending 300 minutes of combined time. Now, let’s say you record a 3-minute Loom with a few focused questions, send it to those same 5 people, and they each take 5 minutes to write their feedback. That’s 8 minutes per person and just 5 minutes once for you. 45 total minutes versus 300. That’s an order-of-magnitude reduction in time to get hyper-focused feedback. 🕒🔍 Just record a quick Loom, pair it with 1-3 specific questions designed to mitigate key risks, and send it to the right people. This async, scrappy approach gathers real feedback throughout the entire product lifecycle (problem validation, solution exploration, or post-launch feedback) without wasting your users' time or yours. Quick example: Imagine your team is torn between an opinionated implementation of a feature vs. a flexible/customizable one. If you walk through both in a quick Loom and ask five target users which they prefer and why, you’ll get a solid read on your overall user base’s mental model. No need for endless scheduling or drawn-out Zoom calls—just actionable feedback in minutes. 🎯 As an added benefit: this approach also allows you to go back to users for more frequent feedback because you're asking for less of their team with each interaction. 🍪 Note that if you haven’t yet established rapport with the users you’re sending the Looms to, it’s a good idea to introduce yourself at the start in a friendly, personal way. Plus, always make sure to express genuine appreciation and gratitude in the video—it goes a long way in building a connection and getting thoughtful responses. 🙏 Now, don’t get me wrong—there’s still a place for synchronous research, especially in early discovery calls when it’s unclear exactly which problem or solution to focus on. Those calls are critical for diving deeper. But once you have a clear hypothesis and need targeted feedback, async tools can drastically reduce the time burden while keeping the signal strong. 💡 Whether it’s problem validation, solution validation, or post-launch feedback, async research tools can get you actionable insights at every stage for a fraction of the time investment.

I’ve been using Cursor to communicate product thinking visually - a quick prototype can speak louder than ten PRDs. But the true game changer I've found is using AI to scale customer understanding. Back at Notion, our team used Enterpret across every stage of building product: 1. Strategy & Roadmapping We brought together feedback from Zendesk, Slack, app store review, social media, Gong, and more. Enterpret automatically categorized themes—top requests, bugs, positive signals—and surfaced them in clean, usable dashboards. Before that, synthesizing feedback was a manual, messy process. PMs spent hours hopping across tools and teams just to find signal. 2. Project Scoping & Validation Once we aligned on priorities, we used Enterpret to dig deeper: What exactly were users asking for? What did they mean? It surfaced quotes, summarized needs, and even helped us identify users for UXR or early testing. The Wisdom feature let us ask questions like: - “What are the top security asks from IT admins?” - “Which integrations do paid customers request most often?” …and get real answers, fast. 3. Post-Launch Sentiment & Closing the Loop After GA, we’d track how sentiment shifted. Did we actually solve the right problems? Who originally asked for the feature—and did we follow up with them personally? Enterpret made that easy, especially for teams without a dedicated UXR or Product Ops teammates. It helped us act faster and more confidently—anchored in real customer signal. If you’re working on similar problems or want to chat about how we approached this at Notion (and now at Enterpret), always happy to connect.

I was just interrupted during our onsite innovation sprint… “I’m sorry, but I don’t think that’s what our customers want.” We’ve been mapping our innovation roadmap all week, and something fascinating keeps happening: Our social team (who absolutely has a seat at the table) continuously brings a critical perspective: “The conversations on social are focusing elsewhere...” “Our listening tools show this is the actual pain point...” “Here’s what customers are saying in real-time...” Their insights can shift our next steps. And they are backed by data from thousands of real customer conversations flowing through social channels every day, unfiltered and honest. So the most valuable question we kept returning to during our onsite was: → Are we building what WE think matters, or what our CUSTOMERS say matters? Your social team isn’t just executing your social strategy - they’re sitting on insights that should be shaping your entire business strategy. How are you integrating social intelligence into your product roadmap? The answers might surprise you.