Customer Needs Product Discovery

Product
Generative Research

Role
Product Partner & Researcher

Tools
1:1 interviews, MS Teams, Miro

Duration
Sep-Oct 2024

Overview

NZTE aims to leverage customer data for better decision-making, but lacks visibility into how customer needs were being captured across the global team. With inconsistent practices between regions and roles, the organisation cannot effectively harness valuable customer insights hidden in their existing data.

I was brought into this project to investigate and document the various formats used by OGT to capture customer needs, understand the reasons behind these practices, and identify whether a consistent, actionable format could be established to enable data-driven insights.

Outputs

  • Formalised initial product assumptions into a research plan with artefacts including a discussion guide, participant tracker, and a collaborative planning workshop.

  • Co-facilitated 9 generative user interviews with Customer Managers across 6 regions and 4 sectors.

  • Synthesised and analysed insights, delivering a clear visualisation of how customer needs were currently documented relative to the existing Customer Way business framework.

  • Created digestible insight summaries and current-state maps for internal product and leadership stakeholders.

  • Summary of insights page 1
  • Summary of insights page 2
  • Summary of key takeaways and opportunities

Impact

🤔 This work provided evidence-based insights that led the Product team to pause and reconsider their initial project direction. It prevented premature investment in changes to the existing CRM structure and avoided introducing new asks or processes to internal teams that wouldn’t align with their day-to-day workflows.

🌱 Beyond addressing the immediate brief, the research surfaced broader operational inconsistencies — such as how market maturity tags were applied — highlighting opportunities for more cohesive, scalable data practices across the organisation.

Notable next steps

  • Sparked a parallel discovery stream into CRM market maturity tags. This led to a refresh of the five market maturity tags, aligned terminology with international best practice, consolidated overlaps, and addressed an 11% gap in existing CRM records.

  • Identified a medium-effort opportunity to embed customer needs data into existing KPI-linked workflows. Through mapping how Customer Managers captured needs, I identified a sustainable way to embed customer needs tracking by adding a new CRM data point alongside Objectives and Actions — fields already tied to team and individual KPIs.

  • Provided foundational insights that informed NZTE’s first AI literacy initiative. When a new AI Product Manager joined shortly after this discovery project, I shared the research findings and customer context gathered through this work. These insights helped surface where AI tools like Co-pilot could meaningfully support Customer Managers’ workflows. A few weeks later, the AI PM launched NZTE’s first AI literacy initiative with an internal pilot focused on Customer Managers — the primary user group from this discovery.

Project Reflections

  • This project reinforced the value of research not only in validating ideas but in constructively challenging them. Delivering insights that contradicted the initial brief required tact and trust, and ultimately helped prevent resource waste while uncovering valuable adjacent opportunities.

  • It also marked a turning point in my relationship with the Product Manager, where I became a true thought partner — a sounding board and co-strategist through open discussion and visual brainstorming sessions that progressed the project beyond its original scope.