AI Leads
AI-driven opportunities, delivered where they matter
Overview
At the start of 2025, I led the design of AI Leads, a major new capability for Matium that transformed the platform into a data-first intelligence product. Previously, Matium’s business model was centered around paid access to Core, with limited functionality for free members. As our network scaled, it became clear that our data was the true differentiator.
Partnering with our Head of Product and Lead AI Engineer, I defined how to surface this intelligence directly into the platform. The result was AI Leads - proactive, AI-driven trading opportunities embedded into the Directory, Haves, and Needs detail pages. Alongside the feature, I helped shape a new pricing model: free members continued to access Core, while paid Intelligence members gained full access to AI Leads. Free users saw a limited preview with blurred cards, creating a clear path to upgrade.
Problem
Although Matium provided a growing network, finding relevant buyers or sellers was still slow and manual. Users had to search, filter, and message repeatedly to uncover opportunities. This friction reduced efficiency and weakened the perceived value of the platform. We needed a way to surface the right opportunities at the right time, directly within core workflows.
Solution
I partnered with our AI engineering and the product team to design AI Leads, a proactive, data-driven feature embedded into key pages like Directory, Haves, and Needs. AI Leads used intelligence from platform activity to automatically surface the most relevant trading opportunities. Users saw curated leads in real time, with free members receiving a preview and paid members gaining full access, turning discovery from a manual task into an integrated, high-conversion experience.
Impact
Positioned Matium as a data-first intelligence platform
Embedded AI-powered leads into Directory, Haves, and Needs
Introduced a new freemium to paid upgrade funnel
First AI-driven lead engine in the raw materials supply chain
Role
Lead Product Designer
Team
Product Management
AI Engineering
Back-end and Front-end Engineering
Company
Matium
Type
B2B
Launch Date
August 2025
Objectives
Surface Relevant Opportunities
We aimed to deliver AI-driven leads directly on key pages that would provide the most relevance to users so they didn’t need to search endlessly to find value. By embedding intelligence into core workflows, we reduced friction and accelerated decision-making.
Scale Trust Through Transparency
AI Leads were designed to feel clear, consistent, and easy to scan, ensuring users understood the recommendations they were acting on. This built confidence in the product while reinforcing Matium’s credibility as a data-first platform.
Promote Conversion Through Value
The gated preview experience allowed free users to see the potential of AI Leads without overwhelming them. By blurring cards and limiting access, we created a tangible reason to upgrade while showcasing the feature’s value.
Discovery
Defining high-value touchpoints for AI-powered leads
Over Q1 and Q2 of 2025, our AI engineering team developed the data pipelines needed to make AI-powered insights possible across the platform. Working closely with them and our Head of Product, I explored how and where these leads could deliver the most value to users.
We identified two key integration points:
Directory Integration: Embedding AI leads directly into our directory so users could see high-value opportunities while browsing the network.
Haves & Needs Detail Pages: Surfacing AI-generated matches on individual listings—whether a user was buying or selling—so leads were tailored to their specific requirements.
This discovery work shaped both the product strategy and the final user experience, ensuring AI Leads felt like a natural extension of existing workflows rather than a bolt-on feature.
Product Strategy
Map AI Data to User Workflows
We collaborated with AI engineers to map where predictive lead data could best serve users. This ensured AI Leads were surfaced exactly where buying and selling decisions were happening—minimizing friction and maximizing impact.
Integrate Across Platform
AI Leads were embedded into the Directory, Haves, and Needs pages so opportunities appeared in the natural flow of user activity, rather than in a separate, isolated experience.
Creating Event Tracking to Measure Impact
We implemented event tracking across AI Leads to capture interactions, engagement patterns, and upgrade behavior. This allowed us to directly measure how often free users converted to the Intelligence plan after engaging with AI Leads, ensuring we could link feature usage to revenue impact and prioritize future iterations based on real data.
AI Leads in Context
AI Leads were introduced across three high-impact areas of the platform. In the Directory, they revealed new companies as potential trading partners. On Haves pages, sellers saw suggested buyers for their available inventory. On Needs pages, buyers were matched with relevant sellers. By embedding intelligence into these workflows, I ensured that actionable opportunities were surfaced exactly where decisions were made.
Designing for Conversion
How we leveraged data for growth
When we launched AI Leads, it became the catalyst for rethinking our entire pricing strategy. Core, which had previously been a paid feature, shifted into our free membership to expand adoption. With that change, Matium began charging not for access to basic functionality, but for the value of its data.
Paid Intelligence members gained full access to AI Leads from day one, while free members saw only a limited preview: a page with five AI Lead cards, one of which was intentionally blurred to highlight what they were missing. This created a clear and intentional upgrade path.
To measure performance, we instrumented key interactions with Statsig, enabling us to track user engagement and optimize conversion paths over time. As a result, AI Leads didn’t just enhance the product experience—it also became a growth driver for Matium’s business model.
Final Thoughts
Since its launch in August 2025, AI Leads has been a welcome addition to Matium’s platform, enhancing how users discover opportunities and make decisions. By embedding AI-driven insights directly into core workflows, the feature created a smoother experience for buyers and sellers while introducing a new layer of value for our paid users.
What went well
The collaboration between design, product, and AI engineering teams was smooth and efficient. With strong technical foundations in place, we were able to focus on crafting a user experience that felt intuitive and seamlessly integrated into the existing platform.
What could have been improved
Under tight deadlines, we couldn’t always ensure the accuracy of the data powering AI Leads. Some contact information occasionally proved misleading, which limited the full potential of the feature until we could refine data quality in later iterations.