Recommendations across digital channels

The problem

The client wanted personalized recommendations across multiple digital channels and several product lines, run as a product that keeps improving rather than a one-off project.

What I did

I owned the product vision and roadmap and led a team of seven across design, data science, machine learning and software engineering, from the design phase to continuous improvement in production. We used data to decide what to improve next.

What I learned

Even a strong value hypothesis doesn’t guarantee results in the real world. So we always ran several experiments at once. That turned “admit failure” into “choose which one to continue”, and nobody lost credibility when an idea didn’t pan out.