During my tenure as a product manager at Rakuten, I consistently grounded the initiation and culmination of all product endeavors in data. This approach dictate

During my tenure as a product manager at Rakuten, I consistently grounded the initiation and culmination of all product endeavors in data. This approach dictated that prior to embarking on any project modifications, the presence of data was imperative to validate (or refute) the underlying hypotheses. This mean that if we just have an hypothesis and no data, we first add hooks to understand the situation throught data (ex. GA events, etc.). For instance, when executives contested the efficacy of our registration form for X reasons, it became incumbent upon us to ascertain its current standing. This involved computing the ratio of registrations to site visits and conducting an in-depth analysis of the errors that users encountered while interacting with the form. We achieved this by integrating Google Analytics events with error messages, among other techniques. We provided first a picture, then we proceeded to make the changes. This systematic approach enabled us to gain a comprehensive understanding of the situation, facilitating the implementation of purposeful changes. Subsequently, we gauged the impact of these alterations using key performance indicators (KPIs) such as the registration-to-visits ratio, and the previous events tracking changes too to understand if we really made a difference.