To close the gap between qualitative and quantitative data is no easy task. Oftentimes these two types of data belong to different, uncommunicated teams. Sometimes a product or experience can bias decision making, by only taking into account one type of data. Nonetheless, symbiosis is important if we are to find the opportunities for continuous improvement. We can use quantitative data to open debate and encourage design research and experimentation. This talk will touch upon the different tools that products can employ to compile data, the different types of quantitative data and how to establish a process resulting in in-depth research, design experimentation and validation. We will discuss some examples of how quantitative data have prompted innovation when paired with qualitative research. As an example, one product I am currently working in is meant to create e-commerce solutions for its clients. A store has three times the conversion rate as other similar ones, resulting in failed design iterations that tried to imitate the appearance of this successful store. However, we changed the way in which this team handled data and developed a process able to explore the motivators of the users visiting this site; this was done particularly by means of contextual interviews, so as to discover how could their needs be satisfied and what was prompting this higher conversion rate, thus being able to replicate this success in other stores.