From Experimentation to Enterprise Readines
The Problem:
Reliant was pivoting product strategies and rapidly needed user feedback — but without reaching users, they were struggling to get it at scale. This growth experiment was designed to recruit our ICP, fast.
Year
2026
Product
Reliant AI
The Challenge
Reliant was in the middle of a product strategy pivot and needed rapid, high-quality user feedback to validate new directions. The challenge wasn’t defining what to test—it was reaching the right users at scale. As a highly specialized B2B product in the life sciences, our ideal customer profile () was both niche and hard to reach. Traditional outbound and network-driven approaches were too slow, while broad marketing channels risked attracting unqualified users.
This created a bottleneck at a critical moment. Without a scalable way to recruit target users, product decisions were being made with limited signal, increasing the risk of misalignment between what we were building and what the market actually needed.
The Strategy
To address this, we designed and launched a growth experiment centered on a high-intent entry point: an AI readiness assessment tailored to life sciences. Rather than asking users for feedback directly, we created a structured, value-driven experience that attracted the right audience while simultaneously generating product insight.
The assessment acted as both a lead generation and discovery tool, anchored in a problem our ICP already felt—uncertainty around how to safely adopt AI in regulated environments.
From a product standpoint, the experience was designed to feel like a product, not a form.
Core components:
Structured assessment capturing:
User workflows
Data maturity
Current AI usage
Backend system to translate inputs into insights at scale
Custom-generated PDF report for each user:
Personalized outputs
Immediate, tangible value
Shareable artifact within organizations
From a growth perspective, it functioned as a wedge—lowering the barrier to engagement while qualifying users based on real behavioral signals.
The Impact
This approach unlocked both scale and quality in user feedback. Instead of relying on slow, manual outreach, we were able to build a steady pipeline of ICP-aligned users engaging with the product in meaningful ways.
Outcomes:
Increased volume of ICP-aligned users
Higher-quality, structured product insights
Faster feedback loops to inform product decisions
Reduced reliance on manual user recruitment
The custom PDF output also increased engagement and perceived value, turning a one-time interaction into a shareable asset within organizations.
Extended impact:
Reports shared internally across teams
Broader reach within target accounts
Stronger early positioning in buying cycles
More broadly, the experiment established a repeatable, productized acquisition channel tied directly to product learning. It created a tight loop between growth and product, where every interaction generated both pipeline and insight—reframing user research from a bottleneck into a scalable system.