[Background] Quality requirements deal with how well a product should perform the intended functionality. Failure to meet essential quality requirements can result in customer dissatisfaction, unusable products, or extra costs. [Objective] The aim is to identify challenges and needs in practice and design solutions for quality requirements engineering which can be applied in practice. [Results] In the two exploratory studies quality requirements engineering practices are investigated. I confirm that some quality requirements fulfillment is not simply being implemented or not, rather evaluated on a scale. Furthermore, some quality requirements are cross-functional. Also, the product lifecycle phase seems to influence both the prevalence and acceptance of quality requirements in the scope decision process. Lastly, relying on external stakeholders and upfront analysis seems to lead to long lead-times and an insufficient quality requirements scope. QREME is a conceptual quality requirements engineering model with a lifecycle perspective. It is built upon a construct with a strategic and tactical level, a product and data dimension to include data in the scope decision process, and a forward- and a feedback-loop to enable a data-driven scope decision process. QREME is validated with five companies in a multi-case study. QREME was able to capture the companies' ways of working and provide relevant improvement recommendations. Also, the presence of the underlying constructs was confirmed. [Conclusions] Quality requirements engineering should be integrated with the overall requirements process. The awareness of quality requirements on a strategic level and catering for the product and portfolio lifecycle are important for success. I conclude that there is potential in sources such as usage data, customer service data, and continuous experimentation to complement stakeholder analysis, expert input, and focus groups. However, there is a need to better understand challenges and needs in practice, especially from a lifecycle perspective. Furthermore, longitudinal studies are needed to evaluate quality requirements solutions over time -- to understand the impact, costs, and benefits.