Building a
Product Org
NetWitness had deep security expertise and no product strategy. I built the operating model, the processes, and the data foundation that changed how the team made decisions.
The Problem
NetWitness builds serious security software: NDR, SIEM, SOAR, EDR. The people running the product org were serious security experts. What they were not was product people, and the gap showed.
There was no product strategy. Roadmap decisions were driven by assumptions, internal opinions, and whoever spoke the loudest in the room. Customer feedback existed in silos across support, sales, and account teams but never got synthesized into anything actionable. The team was shipping based on instinct, not evidence.
The result was a product that was technically capable but increasingly misaligned with what customers actually needed.
Impact
3x
Actionable insights per quarter
After consolidating feedback from 6 sources into Jira Product Discovery
55%
Faster insight-to-prioritization
Reduced time from customer signal to roadmap decision
42%
Fewer post-launch defects
Following structured release readiness and post-launch review processes
89%
Product surface tracked in Pendo
Up from 22% before telemetry instrumentation was prioritized
The Approach
I started with the most fundamental problem: the team had no shared source of truth for what customers were experiencing. Before prioritization could be fixed, feedback had to be centralized.
I built a Voice of the Customer program that pulled signals from every touchpoint, support, sales, NPS, and direct interviews, and routed them into Jira Product Discovery. Trends became visible. Friction points that had been buried in individual tickets emerged as patterns across the customer base.
Alongside that, I worked on instrumenting the product with Pendo to get behavioral telemetry. What customers said they wanted and what they actually used were often different. Having both gave us a real picture.
With the data infrastructure in place, I introduced RICE scoring for prioritization and built out a product strategy that gave the team a framework for making decisions instead of relitigating every roadmap item from scratch. Release readiness processes and SDLC tracking hygiene came next, closing the loop between planning and post-launch learning.
What Was Built
01
Voice of the Customer (VoC)
Built the program from scratch, pulling signals from support tickets, sales calls, NPS responses, and direct interviews into a single discovery layer in Jira Product Discovery. For the first time, the team could see trends across all customer touchpoints, not just the loudest ones.
02
Product Telemetry
Integrated Pendo to instrument real user behavior across the product suite. This gave the team data on where customers were actually spending time, where they were dropping off, and which features were going unused despite appearing on roadmaps.
03
RICE Prioritization
Replaced gut-feel roadmap decisions with a structured RICE scoring model backed by VoC data and telemetry. Assumption-driven roadmap items dropped from over 70% to under 15% within two quarters.
04
Release Readiness
Introduced pre-release checklists and post-launch review rituals that enforced data governance and SDLC tracking benchmarks. Releases went out with defined success criteria, and outcomes were reviewed against them.
The Outcome
The product org went from running on assumptions to running on data. Decisions were grounded in evidence from real customers, backed by behavioral telemetry, and evaluated against defined success criteria after launch.
More importantly, the operating model I introduced created something durable. It was not a one-time cleanup. It was a repeatable system the team could own and improve on, built on tooling and rituals that scaled as the org did.