Scaling product ops at Fabriq with Cycle

Fabriq is a B2B SaaS platform empowering frontline manufacturing teams to drive continuous‐improvement rituals through structured routines, live KPIs, and integrated issue tracking. As Fabriq scaled to 600+ sites across 41 countries, feedback exploded—from Slack threads and Intercom chats to sales call notes and support tickets—creating noise instead of insight. Valuable customer voices were duplicated, lost, or buried in spreadsheets, slowing down decision-making and blurring priorities.

To solve this, Melchior Larere, Fabriq’s Product Manager, set out to build a single source of truth: a self-serve “control tower” where every piece of feedback lands in context, is tagged by customer segment, and flows seamlessly into prioritization workflows—no engineering tickets or data analysts required. By automating ingestion and layering in AI-driven clustering, Fabriq turned fragmented feedback into measurable insights that non-tech users can explore in seconds, fueling smarter road-map decisions and frontline autonomy.

Impact Highlights

• 2× faster feedback triage across Fabriq’s three product units (Shopfloor, Enterprise & Connected Worker)
• 100% feedback-to-problem linkage (up from 50%), so no insight slips through the cracks
• AI-powered clustering slashes manual grouping time by 80%
• Self-serve “control tower” live since April 2025, giving every stakeholder instant visibility
• Customer-impact tracking enabled, now measuring % of users improved (targeting 10–15%)

Use Case: Automating feedback ingestion

Product teams struggled with a scattered and error-prone feedback workflow. PMs were manually copying Slack threads and Intercom messages into spreadsheets—often missing context, duplicating data, or dropping valuable feedback entirely.

What they needed was a reliable, automated way to centralize feedback without losing the original message context—or wasting time.

With Cycle, they replaced the manual process with a efficient ingestion workflow. Feedback now flows directly from Slack and Intercom into Cycle, keeping source context intact and locking key fields against accidental edits. Each submission is auto-tagged with the correct customer segmentation data, ensuring feedback is properly routed and actionable from day one.

"Ingestion time plunged from about 3 minutes per thread to under 45 seconds—and now we can pre-discover feedback right in Slack and, with one click, ship actionable insights into Cycle. Everything’s clean, structured, and instantly trustworthy"
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Melchior Larere - Product Manager @Fabriq

Cycle's flexible feedback pipeline continues to evolve with their needs, helping the team save time, reduce errors, and focus more energy on solving the right problems.

“It’s magic to see all feedback land in one place—and even better to have the tools you need right there to analyze, prioritize, and ship.” – Melchior

Use Case: Building the feedback control tower

Feedback lived in silos—buried in Slack threads, support tools, and spreadsheets. Leadership couldn’t break it down by product line, customer segment, or status. Spotting trends or bottlenecks was near impossible.

"It felt like flying blind, We had the data, but no visibility. No way to zoom out and see the big picture."

Rodolphe Orban - Product @Fabriq

Cycle changed that. By centralizing every piece of feedback into a single source of truth, and powering it with flexible filters and segmentation, Cycle gave teams their control tower. In seconds, leaders could slice data by product area, sentiment, account size, or even support tier—no spreadsheet wrangling required.

“Suddenly, we could track feedback themes across product areas and teams,” the PM added. “And we didn’t need a data analyst to do it.”

Cycle's dashboard gave real-time visibility on volume, velocity, and voice of customer—turning scattered feedback into strategic insight.

Use Case: Doubling the speed of insight discovery

The team also struggled with clustering. Manually reviewing hundreds of feedback items took days. By the time themes were identified, the moment to act was often gone.

With Cycle’s Autopilot, AI analyzes every new piece of feedback as it lands—identifying patterns, grouping similar quotes, and proposing clusters without any manual tagging.

"Clustering that used to take us two days now happens in minutes, we’re moving faster, reacting quicker, and making better roadmap calls."

Product team @Fabriq

Cycle’s AI became a force multiplier—helping the team catch early signals, reduce noise, and double their discovery velocity.

Team-Wide Impact

• Faster decision loops: From feedback receipt to road-map alignment in 48 hrs (vs. 2 weeks)
• Better stakeholder trust: Transparent status updates via shared dashboards
• Empowered non-tech users: No engineering tickets needed for workflow tweaks
• Data-driven prioritization: Quantitative volume metrics replace gut calls

"Cycle unlocked our feedback engine—what used to take days now happens in a few clicks. We’re scaling smarter, not harder."
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Melchior Larere - Product Manager @Fabriq