Fadila Fidina

A requirement arrived with a simple solution: add stricter address validation so customers cannot proceed with invalid addresses.

But this address form lived inside critical payment and ordering flows, where adding friction could harm payment completion, purchases, and customer experience.

In this talk, I’ll walk through a production case study of how we reframed the problem from “prevent invalid addresses” to “collect more valid addresses,” explored address autocomplete as a lower-friction solution, defined success and guardrail metrics, and chose a release strategy that helped us learn without putting the funnel at unnecessary risk.

Attendees will leave with three practical questions they can apply to their own frontend work: what are we really building, what impact are we looking for, and how should we release it?

Shipping a new feature is easy. Knowing if it actually improved anything? That's the hard part.

In production React applications, small UI changes can have a big impact on user behaviour. A new form, validation change, onboarding step, checkout flow, or performance improvement might reduce friction - or quietly make the experience worse.

Many teams still ship these changes based on intuition rather than evidence. Without measurement, it is impossible to know whether users succeeded more often, where they dropped off, or whether the change created unintended consequences.

This talk makes the case that experimentation is part of frontend engineering. Engineers are not only responsible for building the interface; we also help define what success looks like, add the instrumentation that makes behaviour visible, and release changes in a way that lets teams learn safely.

In this talk, we’ll walk through the experimentation lifecycle from a React engineering perspective: forming a hypothesis, defining success and guardrail metrics, instrumenting meaningful user behaviour, gathering data through feature flags or staged rollouts, and learning from the results.

Attendees will leave with a practical framework for embedding experimentation into React feature delivery, so teams can build confidence in the true impact of what they ship.