Enterprise Product Feedback Loop

• "We need better latency" from a trading firm vs a marketing agency means very different things
• GDPR region customers have different compliance needs
• Strategic partners deserve faster response times
• Patterns within segments reveal product opportunities

When Each Category Matters Most

Tagging Strategy

Every piece of feedback should be tagged with:

⚡ Quick Wins (Low Effort, High Impact)

1. Slack emoji reactions → Notion (use Zapier, takes 30 mins to set up)
2. Weekly AI digest of customer Slack channels (copy/paste into Claude, 10 mins/week)
3. Linear status changes → customer Slack notification (native integration)

🎯 The Philosophy

AI handles the routing, deduping, and summarizing. Humans own the judgment, storytelling, and decisions. The goal is to get from raw feedback to actionable insight faster—not to outsource your thinking.

⚠️ Where AI Should NOT Replace Humans

• Prioritization decisions: AI can score, but humans decide what to build
• Strategic trade-offs: AI doesn't know your roadmap constraints or vision
• Customer relationships: Closing the loop requires human judgment and empathy
• Verification calls: AI can suggest questions, but humans build trust
• Saying no: AI can flag what's low-value, but the PM owns the conversation

💡 Getting Started with AI Triage

1. Start with one channel: Pick Slack or support tickets, not everything at once
2. Build the prompt library: Test categorization prompts on 50 real examples before automating
3. Human-in-the-loop first: Have AI suggest categories, humans confirm for first 2 weeks
4. Measure quality: Track agreement rate between AI and human reviewers
5. Add channels gradually: Once one channel works, add Granola, then support, then GitHub
6. Weekly calibration: Review AI mistakes weekly and update prompts

🚨 Common Failure Modes

• Over-engineering: Don't build a complex system before proving the process works manually
• No ownership: Someone (Product Ops?) needs to own the system, or it will decay
• All capture, no action: If feedback goes into a black hole, people stop contributing
• No exec sponsor: Without leadership buy-in, Sales won't prioritize logging feedback

📅 Suggested PM Discovery Rhythm

❌ The Mistake

Survey all users → Get averaged-out, contradictory feedback → Build features that half-satisfy everyone and fully satisfy no one.

✅ The Solution

Segment users by behavior, then ask targeted questions to the right cohort.

❌ Why Surveys Don't Work

• Low response rates from busy enterprise users
• Answers are sanitized and polite, not honest
• They interrupt the user's flow
• Users tell you what they think you want to hear

💡 The Best "Survey" Is Part of the Product

• Feedback button in context: Small "Feedback on this feature?" link on every page—not a popup, just there if they want it
• After task completion: Optional thumbs up/down—"Did this work as expected?"
• When they search and find nothing: Log the search query—this IS the feature request
• On cancellation: Single open-text field—"What would have changed your mind?"

"When customers point to the moon, the naive product manager examines their finger."

The "faster horses" tale is often used to justify not listening to customers, but that misses the point. If a customer says they want a faster horse, they're telling you speed is a key requirement for transport. Your job is to figure out how to deliver that—which might be a car, not a faster horse.

❌ The Trap

Five users ask for a simpler event form → Team immediately kicks off "event simplification" project → Ships feature that 5 users love and 500 ignore → Wasted effort.

✅ The Right Approach

Five users ask for a simpler event form → Treat this as a hypothesis → Talk to 20 more calendar users → Discover the pain isn't form complexity but how often they have to fill it out → Build recurring events and easy duplication instead.

🎯 When to Trust Your Gut

Occasionally a feature request will be spot on. It rhymes with everything else and perfectly fits the world the way you see it. On these occasions, you can skip steps—verification, abstraction, clustering—and trust your intuition.

This shortcut only works if:

• You're still a true user of your own product
• You're constantly in touch with the needs of your users
• The request genuinely "clicks" with your product vision

But on every other occasion: talk to your customers. It makes you smarter.

⚠️ Watch Out: Segment Gaps

Before acting on feedback, check your coverage:

• Do we have enough feedback from each model (Large, Small, Codestral)?
• Do we have enough from each industry (Finance, Healthcare, Tech)?
• Do we have enough from each region (if relevant)?
• If a segment is under-represented, actively seek their input before deciding.

💡 The Verification Checklist

• ☐ Hypothesis written down (not just a feature name)
• ☐ Talked to 3x the original sample (5 requests → 15 conversations)
• ☐ Pain came up unprompted in >50% of conversations
• ☐ Understood the job-to-be-done, not just the feature ask
• ☐ Abstracted above the literal request to the underlying need
• ☐ Checked segment representation is adequate
• ☐ Quantified impact (users affected × frequency × severity)
• ☐ Solution addresses the real problem (may differ from request)

Why Airtable?

• Flexible schema: Add fields as you learn what matters
• Multiple views: PMs, Sales, and Eng each see their own view of the same data
• Easy enrichment: Link to customer records for segmentation
• Automations: Trigger Slack alerts, sync to other tools
• Reporting: Built-in charts for trends and coverage

🔴 Red flag if any segment has < 15 data points—actively seek more input before deciding.

💡 Getting Started

1. Create the base with the three tables (Feedback, Customers, Themes)
2. Import your customer list from Salesforce (CSV export)
3. Set up a Slack → Airtable Zapier to capture emoji-reacted messages
4. Create the four role-based views
5. Add the coverage charts to spot gaps
6. Start logging—even manually at first—to build the habit