AI Matching

The problem

A freelancing marketplace lives or dies on the quality of its matches. If a client has to scroll through dozens of profiles, or a freelancer has to hunt for projects that fit, both sides lose patience and leave. Ditansource, a United States based marketplace, needed to shorten the path to the right match while also growing its user base.

How I approached it

As the product management consultant I started by looking at what makes a good match from both sides: the skills and context a client cares about, and the kind of work a freelancer wants. I then introduced AI matching into the core flow so that projects and talent are connected automatically, rather than relying on manual search alone.

In parallel I worked on the funnel that brings people in. I optimized the LinkedIn-to-website journey and its conversions, and led a five-person marketing team, setting campaign priorities and guiding day-to-day execution so that product changes and acquisition pushed in the same direction.

The outcome

AI matching automatically connects freelancers with the right projects and helps clients find the right talent, while the funnel work grew the user base by 6,000+ new users in a single week.

What it taught me

Growth and product are one system. Better matches only matter if enough of the right people arrive to be matched.