Technology-oriented innovative startups must conduct extensive experiments to gather sufficient proofs of value, so that they may reduce uncertainties before the launch of their products and services on the market. Despite their limited resources, the experiments conducted by startups are often random, loop-based and consequently time and resource consuming. Hence, startups need solutions to help them better planning their technology maturation and identifying market opportunities. It is in the context that the current research is carried out.First, a literature review is conducted in the fields of engineering design, technology management and innovation management. This review suggests that the existing methods and tools fail to provide accurate and quantitative roadmaps to conduct relevant experiments. Second, this research surveys the design and testing practices of 60 innovative startups in the context of the City of Paris. This investigation reveals that despite the use of popular innovation methods such as Business Model Canvas (BMC) and Lean Startup, startups have no practical tools for specifying and planning experiments, nor for efficiently using their resources.Therefore, this research makes the following three contributions. First, the BMC tool is combined with quantified value buckets (opportunities) and innovativeness indicators in order to make sure that the value offer is effective and significant. Second, a Design by Usage-based Experimentation (DUE) methodology is proposed to help screening the whole set of potential markets and to identify the main technology properties that need to be improved through experiments. Third, a quantitative methodology called RITHM (Roadmapping Investments in TecHnology and Market) is proposed to optimize the set of experiments, so that they result in the maturation of a technology to reach the most profitable markets. The relevance of the proposed methodologies is assessed through their application to technology-oriented innovative startups and also through expert validation. Finally, this research concludes that it is possible, with more effective and economical R&D strategies, to better define experiment roadmaps and better steer technological startup investment.This research may significantly support the decision-making process of various actors: entrepreneurs, who need to justify R&D expenses in fund-raising applications; public and private investors, who constantly tend to minimize investment risks in innovative technologies; or technology scouts.