Web browsing is one of the most popular applications for both desktop and mobile users. A lot of effort has been devoted to speedup the Web, as well as in designing metrics that can accurately tell whether a webpage loaded fast or not. An often implicit assumption made by industrial and academic research communities is that a single metric is sufficient to assess whether a webpage loaded fast. In this paper we collect and make publicly available a unique dataset which contains webpage features (e.g., number and type of embedded objects) along with both objective and subjective Web quality metrics. This dataset was collected by crawling over 100 websites-representative of the top 1 M websites in the Web-while crowdsourcing 6,000 user opinions on user perceived page load time (uPLT). We show that the uPLT distribution is often multi-modal and that, in practice, no more than three modes are present. The main conclusion drawn from our analysis is that, for complex webpages, each of the different objective QoE metrics proposed in the literature (such as AFT, TTI, PLT, etc.) is suited to approximate one of the different uPLT modes.