About the Client
A fast-scaling AI company building enterprise-grade machine learning tools approached Nexus while preparing to launch its next product: a new platform designed for automated data labeling and model training. While their internal R&D team had confidence in the tech, the leadership team needed to understand how the product would be received by real-world buyers, ML engineers, and competing vendors across industries like healthcare, finance, and manufacturing.
The Challenge
Need for Insight Across Technical and Commercial Roles
The client didn’t just want buyer feedback; they needed perspectives from machine learning engineers, AI heads, data scientists, and procurement leads to understand how technical usability and purchasing decisions worked together.
Highly Competitive and Evolving Market
In the crowded AI tooling space, new startups and incumbents were launching weekly. The client wanted to test differentiation, pricing, and adoption friction before committing to a broader go-to-market plan.
Our Approach
Targeted Expert Matching by Role and Sector
We sourced and vetted over 50 professionals across the U.S., EU, and APAC, including ML engineers at large enterprises, CTOs at AI-first startups, and enterprise buyers who had evaluated or implemented similar tools.
22+ In-Depth Qualitative Interviews
Our team facilitated structured 1:1 calls covering usability, deployment time, integration with common pipelines, pricing sensitivity, and value perception. We also explored how competitors were positioning their platforms in similar segments.
Thematic Synthesis for Product & Sales Teams
We grouped insights by theme (deployment friction, model performance benchmarks, sales blockers, etc.) and segmented them by user type (technical end-user vs. business buyer). This helped the client see which value propositions resonated with whom.
Fast Turnaround to Match Internal Launch Timeline
Given the client’s roadmap, we delivered all interviews, transcripts, and a summary insights deck within 18 business days, giving the product and go-to-market teams time to pivot where needed.
Results & Impact
Thanks to expert input across roles and industries, the client:
- Reworked key onboarding workflows based on engineer feedback, reducing time-to-first-use by approximately 30%.
- Identified two industries (healthcare & logistics) where their platform had clear differentiation and strong near-term demand.
- Adjusted pricing tiers to better fit enterprise buyer expectations uncovered during calls.
- Used expert testimonials and quotes in internal materials to secure board-level support for the updated go-to-market strategy.
The client now partners with Nexus for strategic insight across AI safety, enterprise tooling, and international market entry.
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