the tokoboard
Your PMs Favorite Product is here! I built Toko because getting good product feedback sucks when you’re moving fast. I wanted a way for teams to run what feels like a real conversation with their users without scheduling calls, and still walk away with clear, organized insights and a community they can actually use.
Right now, most early-stage teams rely on one of two feedback channels:
Slack threads / quick polls — fast, but shallow
Live user interviews — deep, but painfully slow
Just last week, I watched a founder friend collect product feedback in Slack for their YC startup. It looked nice, but the responses were vague — mostly thumbs-up emojis and “looks good!”
So what happens?
They run interviews instead.
But every founder knows: interviews are an 80-minute time sink each. Imagine reclaiming those hours when you’re racing toward your next sprint deadline.
The problem:
Fast channels = shallow signal
Deep channels = unscalable
The faster your team moves, the harder it is to keep user context front and center. And bad context leads to bad product bets.
One line from a mentor at Blibli (PM for the #1 e-commerce site in Indonesia) stuck with me:
“Every $1 invested in good feedback returns $100.”
So why should it be a choice between speed and depth?
We saw the same pattern with a friend’s YC startup, Daymi:
Too many features shipped without validation
Reliance on founder intuition over data
Spoiler: Toko’s beta has already been tested with 5 YC/SkyDeck startups and 45+ early-stage teams.
📋 Research → 🧠 Synthesis → 💻 Design → 🔁 Iterate
Over 3 weeks, I built and shipped an MVP from scratch while running targeted research with PMs and founders.
We knew the “lightweight feedback” space was dominated by Google Forms, Typeform, and random Slack integrations. On the other side, full-on user research platforms like Maze or Dovetail offered depth, but were intimidating for scrappy teams.
Guiding question: How do we give teams depth and speed without the bloat?
From 20+ founder interviews, three consistent blockers emerged:
Low awareness / visibility — “I just thought it was another survey bot.”
Perceived complexity — “Research tools are always clunky or need setup.”
Low trust in AI — “Is this actually going to give me insights or just dump a CSV?"
I segmented users into three buckets:
⭐️ No experience with automated research tools — want frictionless onboarding
⭐️⭐️ Tried basic forms or polls — want more context, less admin work
⭐️⭐️⭐️ Paid for full research suites — want speed without losing rigor
After 28 founder/PM interviews and live tests, patterns became clear:
User quotes:
🟢 “Follow-ups felt like an actual teammate asking questions.”
🟢 “Way less intimidating than the big research tools.”
🟢 “Loved the chat flow — got richer answers from my beta testers.”
But:
🔴 “Still feels like a fancy survey at first glance.”
🔴 “Didn’t realize it could auto-tag and summarize.”
🔴 “Wasn’t sure if I was running a survey or an async interview.”
Feedback Board, Commuity Announcements and Progress Transparency Interfaces
Conversational Feedback Sessions
Chat-style interface that feels like a real conversation, not a static form — making responses richer and more honest.
Context-Aware Follow-Ups, FAQ Generator, and Quick Answers
AI dynamically asks smarter, relevant follow-ups, FAQ pages, and answers to product questions based on what’s already been said and used by toko agentically.
Auto-Suggestions & Multi-Agent Interaction
Built-in suggestion engine and multiple AI “personas” that can guide, probe, and enrich the conversation in real time.
Semantic Tagging & Instant Insights
Automatic theme detection and tagging so teams get shareable, ready-to-use insights without sifting through raw transcripts.
