Building what customers need, not just what they ask for
Notes from our product team on building the tools we use every day.
Steve Jobs famously said customers don't know what they want until you show it to them. Henry Ford quipped that people would have asked for faster horses, not automobiles. Yet at Linear, we just built a feature specifically designed to collect customer requests. Seems contradictory, right?
It's not. Here's why.
The feedback paradox
Product teams face a fundamental tension. Build only what customers ask for and risk mediocrity. Ignore feedback entirely and risk irrelevance. Every product decision exists within this practical challenge.
The most innovative products emerged without explicit customer requests. Nobody asked for the first iPhone, Airbnb, or Figma. These products came from vision and intuition.
Meanwhile, the graveyard of failed startups contains countless visionary products nobody wanted.
Feedback sharpens intuition
At Linear, we believe the best products come from strong opinions informed by customer reality. Customer feedback serves as the whetstone that sharpens intuition, rather than the source of product vision.
Users rarely articulate their core problems directly. They describe symptoms, request features they’ve seen elsewhere, or suggest solutions that address their specific need but wouldn't serve the broader user base effectively.
When a user asks for "custom fields," they're expressing a deeper need that requires interpretation. Just as a doctor doesn't make accurate diagnoses by collecting more patient self-diagnoses, product teams don't create successful products by simply amassing feature requests.
The magic happens in the interpretation. The most valuable skill in product development lies in understanding what remains unsaid, beyond the explicit feedback.
Why we built Customer Requests
So, why build Customer Requests if raw feedback alone misses the mark?
Customer feedback, when collected thoughtfully, organized intelligently, and interpreted skillfully, becomes a powerful intuition amplifier.
Feedback becomes fragmented at scale
We observed a consistent pattern across growing companies. When teams are small, customer understanding happens naturally. Engineers chat directly with users, support teams recognize repeat requests, and everyone develops an intuitive feel for customer priorities through proximity.
But scale changes everything. Customer conversations multiply and fragment across email threads, support tickets, Slack messages, app store reviews, and research calls. What was once a clear signal becomes buried in noise. The small-company systems that worked at the start begin to fail under this volume.
Capturing feedback isn't the problem. Sales teams use Gong, support uses Intercom, and product teams maintain separate research repositories. The challenge appears when product teams need to use this feedback. They spend hours navigating multiple systems, many of which they lack access to, trying to piece together fragmented context.
I love seeing customer feedback — it brings our work to life. While we get great insights from UX interviews and our customer-facing teams, sometimes valuable feedback gets stuck in tools I can't access.
When product teams lack deep customer understanding, they explore paths that don't address core customer problems. For larger companies especially, this creates significant waste — engineering resources go toward features that customers don't need while crucial problems remain unsolved.
Reading between our own lines
We experienced this pattern firsthand. When users requested "custom fields," we dug deeper to understand the underlying need rather than implementing the feature at face value. Conversations with users revealed that approximately 40% wanted these fields specifically to track customer needs. Adding a simple custom field felt like a bandaid to a bigger problem — instead, we created something purpose-built that solves this specific problem exceptionally well — a dedicated workflow connecting customer context directly to product decisions.
We created a dedicated space in Linear, displaying customer context alongside engineering work. Customer needs weren't just abstract requests anymore, and they didn't get buried. These were real companies with real people, positioned alongside actionable engineering work.
Support tools often have the highest density of customer feedback. When product and support teams get closer together, and the systems between them are smooth, magical things happen.
Our Customer Requests feature brings feedback from support tickets, Slack messages, and calls directly into Linear – where product and engineering teams can spot patterns, interpret needs, and build context that informs decisions.
We designed it to move beyond tallying votes for features — providing teams with concrete data to recognize patterns and build products users actually need.
Customer Requests enables teams to:
- Bring the voice of customer directly into product development
- Prioritize high-impact needs by filtering customers by revenue, tier, and other business metrics
- Replace scattered tracking methods and eliminate manual syncing between tools
Where we're heading
When we started building Customer Requests, we set out to solve a clear problem — help growing companies stay as close to their customers as they were when small.
We're working on integrating with Salesforce and HubSpot so teams can capture customer context where they already work. We'll use AI to help teams find the signal through the noise and make sense of all this feedback.
The best products emerge when strong vision meets deep customer understanding. Pure customer-led development and isolated visionary thinking both fall short of consistently producing breakthrough products. Develop your product intuition by immersing yourself in customer feedback while trusting your ability to see patterns and needs they cannot articulate. Treat customer requests as input, not instructions.
