Since the introduction of micromobility operations, cities across the country have endeavored to foster and shape these services to support city goals while also facing rapid change and unfamiliar business models. Evaluating and understanding the data generated by these services is a necessary step toward identifying whether these services are helping or hampering city goals. Given the nascent stage of the micromobility industry, however, cities so far have mostly used operations and trip data generated by operators to track and learn how micromobility services are being used and determine if operators are complying with municipal regulations. As micromobility services proliferate, and as their use grows and evolves, different methods are becoming necessary for better evaluating how these services are directly contributing to outcomes desired by both cities and operators. Cities can lead in strategically integrating micromobility services to achieve community-based, long-term outcomes by establishing clear targets, informed by partnerships with micromobility operators and other key stakeholders, for these services, and basing the data cities need directly on measuring these outcomes. This approach will not only assure outcomes are being tracked appropriately, but also that the data are used effectively while protecting the privacy of users. To keep outcomes at the forefront of the process, this website has been divided into sections addressing the following common, high-level outcomes agreed upon by the working group: Equity Safety Environment For each of these outcomes, there are myriad use cases and metrics that could be created using available data. To simplify and prioritize, the working group identified example goals within each outcome area along with key questions to distill the possibilities down to what is thought to be most important at this point in the evolution of micromobility services. For each question, we have included “evaluation” metrics to measure progress toward the above high-level outcomes. Each section also includes example policy levers that are within cities’ purview to effect change on those outcomes, as well as “policy” metrics to measure whether those chosen policy levers are achieving their desired effect. Though analyzing every question or metric offered in this website would be a daunting task for any agency or local government, the goal for the working group was to be as comprehensive as possible. Given the breadth and depth of the suggested metrics, it will be incumbent upon local governments and agencies to determine which metrics are most pertinent to the goals and outcomes they are prioritizing for their communities. When choosing metrics to apply locally, cities should account for the interconnected nature of all these outcomes as well as other factors not directly addressed in this website. To help cities and agencies determine which data is most important to collect when developing a pilot program or permit regulations, Remix, has helped identify the specific data necessary to inform each metric throughout this website. It is important to note that the data identified for the proposed metrics within this website were chosen in an effort to minimize collected data, personally identifiable information (PII) and risks to privacy. While the underlying raw data collected from providers inherently contains privacy risks, no output from any metric included in this website should pose a risk to privacy in itself. In this case, the risk to privacy isn’t in the output of any specific metric, but in holding the raw data. But, to obscure individual trips, analysis should be framed over a large enough arc of time or geographic area that not only protects individual user privacy, but also allows for consistent findings across time and space. Local governments and agencies will need to make sure their data storage, access, management and security processes comport with their state and local data regulations. Lastly, while data generated by micromobility services can provide new insights, there is much more that we desire to understand outside of the scope of data. At its best, micromobility data generated by services or provided through user surveys can only provide a partial picture. The missing pieces can only be illuminated by engaging local residents and interacting with riders directly through public meetings, personal conversations and other engagement strategies. And, given micromobility’s nascent stage, it will be important to confirm the data and any information gained from direct engagement with on-the-ground observation such as video analytics, count programs, etc. to ensure these findings comport with reality. It is also important to recognize that shared micromobility data on its own provides only a small portion of the larger transportation reality, as cars, trucks, transit and other motorized vehicles contribute the vast majority of trips in many cities.